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Why Smaller Firms Are Getting Hammered: Myths of Scale

Why Smaller Firms Are Getting Hammered: Myths of Scale

There is a bit of folklore in most heavily regulated industries, and especially in the financial services industry, that goes something like this: Larger players should worry the most about regulatory compliance and security.
The reasoning is simple: Larger, well-known firms are the ones most likely to be targeted by both cyber criminals and government agencies. Smaller firms—even moderately sized ones—will tend to “fly under the radar” of both, and so can put off investing in technology (RegTech) or training until the time when they have grown big enough to attract attention. In short, worrying about compliance or cybersecurity is a matter of scale, but only in the roughest sense: There are two size classes, bigger firms that need to worry about these things, and everyone else.
The term “folklore” is apt here because this kind of thinking never is written explicitly, but it is assumed by many. And while it might have applied in the past, it is surely not the case now—which means that too many regulated firms are toiling under a false, and risky, assumption.
With Automation, Everyone is On the Radar: The Ransomware Example

So what has changed?

Let’s look at the logic with a specific example: Ransomware gangs that try to gain a foothold in a business to take a chunk of the firm’s data hostage.
Not too long ago, gaining access to critical business systems took some time and diligence on the part of the hackers. They had to either undo the company’s security and encryption, or else dupe an employee into giving up their credentials (easier to do, the more employees there are). Because an attack took time and effort, it made sense for hackers to go “big game hunting”—that is, to try to get the best bang-for-their buck by targeting larger firms with bigger cash flows. That is where the best payoff would be.
What has changed since those days is automation. A ransomware gang can now target hundreds of firms of various sizes, all at the same time, looking for vulnerabilities and beginning spear-phishing attacks to gain system access. They can then focus their energies on those that prove vulnerable, even if the payoff is much less for any one successful attempt.
And which firms tend to be the most vulnerable? It is exactly the small-to-medium-sized firms, because they have bought into the folklore that says hackers won’t bother targeting them. Having bought into the folklore, they don’t take the necessary steps to protect themselves.
Think of it as a contrast between a cat burglar and a gang of street thieves: The cat burglar spends his time trying to pick the lock on a single door, hoping there is a stash behind it. But what the gang of thieves lack in skill and finesse, they more than make up for in manpower: They simply try every door, hoping that, eventually, one will be unlocked. The unlocked rooms might not be as lucrative, but they are also much less likely to have adequate security measures in place, too. Today’s hackers are no longer cat burglars, they are gangs looking for easy scores—and smaller firms are exactly that.
Regulatory Compliance is Playing the Same Game
Ransomware is just one example of a risk to which firms of all sizes are now exposed. A similar logic now applies to regulatory compliance, too.
Government institutions, for a long time, went after bigger firms, believing they would be the most egregious offenders when it came to compliance. Smaller firms would not attract much scrutiny, unless something was directly brought to the attention of regulators.
This is no longer the case, and again, automation is part of the story. For example, government firms are now using automation and artificial intelligence to “find the needle of market abuse in the haystack of transaction data,” using various algorithms to scrape the web for deceptive advertising and capturing red flags that might indicate wrongdoing. They are also using these tools to zero in on accounting and disclosure violations. Regulators can now spot potential problems more quickly and quietly than ever before, and now more small firms are getting MRA letters from regulators, surprised that they are no longer invisible.
This is an importantly different phenomenon from regulatory tiering. It has always been the case that many regulations carve out exceptions for smaller businesses, when strict compliance would be an undue burden on them. For example, health insurance mandates and employment laws have clauses that exclude firms of a particular size. While it can be debated how and when such tiering should occur, the fact is that many businesses fall under the more regulated tier by law, but have traditionally escaped scrutiny because they were “small enough.” Those days are now over.
Beware, Data Scales Quickly
Part of the issue for financial services firms is not only the sheer amount of data they generate, but the kinds of data they generate.
The volume of data generated correlates pretty well with the size of a firm. This makes sense: The larger the firm, the larger the customer base, and the more transactions happen every day.
But the compliance nightmare comes more from the huge variety of data generated by financial services firms, and that variety does not scale: It’s huge, whether you are a small local firm or a large international one. For example, on top of transactional data, a financial services firm might have
  • Client personal data (name, address, birthday, Social Security number, etc.)
  • Credit information
  • Mortgage and loan information
  • Contract information
  • Email and other logged communications
  • Employee personal information and pay information
  • Analytics data (based on customer spending patterns, segments, new products, customer feedback, etc.)
  • Marketing data (email open rates, website visits, direct mail sent, cost of obtaining a new customer, etc.)
…and much more. That data often resides on different servers and within an array of applications, often in different departments.
This means that, when it comes to complying with data privacy laws, or protecting data with the right cybersecurity measures, size doesn’t matter. The variety of data is a problem for firms of all sizes.
Moral of the Story: Smaller Firms Need Protection, Too. Yes, You.
The folklore says that smaller regulated firms can put off investment in cybersecurity and RegTech simply because cyber threats and regulatory scrutiny will “pass over” smaller firms and land, instead, on the bigger players.
That is no longer the case. Both cyber criminals and government regulators are using tools to spot problems more quickly and easily, and it is worth their while to set those tools to investigate everyone. (We’ll let readers decide which they would rather be spotted by first.) Indeed, small- and medium-sized firms are having a more difficult time now, because it is much less common for these firms to have proactively invested in preventive solutions.
So what do you do if you are a smaller company in a heavily regulated industry? The first step would be to look into technology that can give you the most protection for your dollar. After all, if cybercriminals and government agencies are going to use advanced digital tools, you should too. Having an immutable data archive, automated compliance workflows, and application retirement tools are all a good beginning.
The alternative would be to do nothing, and hope that your turn will not come up. But strategies based on folklore have never been very good at reducing risks—quite the contrary.

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Legacy Data is Valuable, but Legacy Applications Are a Risk. What’s a Finserv IT Department to Do?

Legacy Data is Valuable, but Legacy Applications Are a Risk.
What’s a Finserv IT Department to Do?

In January 2022, infosec and tech news sources blew up with stories about “Elephant Beetle,” a criminal organization that was siphoning millions of dollars from financial institutions and likely had been doing so for over four years.
This group is sophisticated. It is patient. But the truly frightening part of the story was that the group was not using genius-level hacking techniques on modern technology. On the contrary: Their MO is to exploit known flaws in legacy Java applications running on Linux-based machines and web servers. Doing this carefully, the group has been able to create fraudulent transactions, thereby stealing small amounts of money over long periods. Taken altogether, the group managed to siphon millions unnoticed.
What this story reveals is that legacy applications are a huge liability to financial institutions. They have known vulnerabilities that, too often, go unpatched, and they can be exploited without raising an alarm.
Even if they are not breached by bad actors, such systems can be a drag on institutional resources. According to research done by Ripple back in 2016, it was estimated that maintaining legacy systems accounted for some 78% of the IT spending of banks and similar financial institutions.
The question is: Why are financial institutions holding onto these legacy applications? And what can be done to minimize the risk they pose?
The Need to Retain Legacy Data
Most companies have at least one legacy application they still support simply because they need its data. In some cases, that data has to be held to fulfill retention requirements for operational or compliance purposes. In other cases, that data holds important business insights that can be unearthed and used profitably. And in some cases, it’s a mix of both.
But with the march of technological progress, it’s easy to see how this situation can get out of hand. Some organizations have hundreds of legacy applications they’ve accumulated over time just to keep easy access to the data stored within them. The vast majority of those applications are no longer being fed live data, having been replaced by next-generation solutions. But they sit on the organization’s network just the same, taking up resources and allowing bad actors to have a back door to other more mission-critical applications.
Because these applications are no longer in use or are being updated with new data, it does not make sense to patch and maintain them continually. (And in most cases, patching is not even an option as no one is supporting the legacy application anymore.) To really make them safe, they should instead be retired. Application retirement, done correctly, can render an application inert while still providing select users access to its data.
Application Retirement is Now a Part of Finserv IT Best Practices
Application retirement is the process used to decommission applications (and any supporting hardware or software) while securely keeping their data accessible to maintain business continuity. As applications grow, develop, and change, the number of legacy applications that need to be carefully retired grows exponentially.
An application retirement program is simply a strategy, including a schedule and a set of rules, for ensuring that application retirement happens correctly. Any application retirement program must ensure that the right data is retained and in the correct business context so that the data remains meaningful to business users (or auditors) long after the legacy application is decommissioned.
More and more businesses are looking for increased sophistication when it comes to such programs because they provide:
  • Direct savings by eliminating legacy support and maintenance costs (which, again, can account for 78% of financial institutions’ IT budget).
  • Efficiency gains by delivering effortless access to historical business data.
  • Regulatory compliance through application retention rules that manage data securely throughout its lifecycle.
That said, the most challenging part of a retirement program often is getting it off the ground. Getting leadership buy-in, determining retirement criteria, and classifying all of the applications in the ecosystem can produce hurdles to effective execution.
And even when those hurdles are cleared, the process itself takes a great degree of technical expertise to execute. System analysis; data extraction, processing, and storage; user access design—all of these need to happen seamlessly before the application itself can be successfully retired.
Getting the Expertise on Board for a Successful Application Retirement Program
We’ve only scratched the surface here regarding best practices around application retirement. Those interested in learning more about the application retirement process and the best practices around a robust application retirement program are encouraged to download our white paper: Application Retirement: The Practical Guide for Legacy Application Maintenance.
But even with this quick glimpse, two things are already clear. One is that it takes a good deal of technical know-how, as well as best-in-class tools and technology, to successfully retire applications while still making the critical data within them accessible.
The other is that relying on the status quo is simply not a viable option. While the organizational and technical hurdles to proper application retirement are substantial, their cost is far outweighed by the cost of doing nothing—which includes not only wasting valuable IT department time and budget but also leaving the back door open to bad actors.
Interested in tools that make application retirement easier? Ask us about Infobelt’s Application Retirement Workbench, available with Omni Archive Manager.

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The Future of Artificial Intelligence in Data Preservation and Business Records Management

Infobelt

The world is experiencing an unprecedented explosion of data, with businesses generating massive amounts of information daily. Efficiently managing and preserving this data has become a paramount challenge for enterprises seeking a competitive edge in the digital age. Enter Artificial Intelligence (AI), a technology that promises to revolutionize data preservation and business records management. In this blog post, we will explore how AI is shaping the future of data preservation and transforming the landscape of business records management.
1. AI-Driven Data Preservation
Data preservation safeguards valuable information to ensure its longevity and accessibility over time. As the volume and complexity of data continue to increase, traditional data preservation methods need to be revised. However, AI is changing the game by offering intelligent solutions enabling businesses to manage their data preservation needs proactively. Machine Learning (ML) algorithms can analyze patterns in data usage, predict potential issues, and optimize storage, ensuring critical information is safeguarded against loss. Additionally, AI-driven data preservation systems can automatically detect and repair corrupted files, reducing the risk of data degradation over time. By leveraging AI, businesses can achieve cost-effective, scalable, and reliable data preservation, supporting the seamless functioning of organizations across industries.
2. Enhanced Data Classification and Organization
Effective business records management requires precise data classification and organization. Traditionally, this task has been labor-intensive and error-prone. However, AI-powered data classification tools can analyze vast amounts of unstructured data and accurately categorize it based on predefined parameters. Natural Language Processing (NLP) algorithms can extract critical information from text-based records, such as contracts, invoices, and legal documents. Image recognition capabilities can help classify visual data, including scanned documents and images. These AI-driven tools streamline records management processes, enabling businesses to quickly locate and retrieve essential information, resulting in improved operational efficiency and compliance.
3. Intelligent Data Retention Policies
Developing data retention policies that comply with legal and regulatory requirements can be complex. Failure to adhere to these policies can lead to severe consequences, including fines and reputational damage. AI can assist in crafting intelligent data retention policies that automatically adapt to changing regulations and business needs. By analyzing historical data usage patterns and monitoring regulatory updates, AI systems can recommend appropriate retention periods for different types of records. As a result, businesses can strike a balance between retaining valuable data for historical analysis and disposing of obsolete information in a compliant manner.
4. Predictive Analytics for Better Decision-Making
AI-driven predictive analytics transforms how businesses make decisions by providing valuable insights based on historical data and real-time inputs. By analyzing records and detecting trends, AI can forecast potential risks and opportunities, aiding businesses in strategic planning and risk management. Moreover, AI-powered analytics can identify anomalies in financial records, supply chain operations, and customer behavior, thereby mitigating the impact of fraud and irregularities. These proactive measures can prevent financial losses and protect an organization’s reputation.
5. Automation of Records Management Processes
AI-driven automation is at the core of the future of records management. Repetitive and time-consuming tasks such as data entry, document indexing, and content retrieval can be efficiently handled by AI-powered robotic process automation (RPA). RPA bots can interact with multiple systems and applications, ensuring seamless integration across various data sources. This level of automation saves time and resources and minimizes human errors, resulting in increased data accuracy and compliance.
6. Data Privacy and Security
Data privacy and security are paramount concerns for businesses dealing with sensitive information. AI plays a crucial role in bolstering data protection measures. AI algorithms can continuously monitor networks for potential threats and quickly respond to security breaches. Additionally, AI-powered encryption techniques can safeguard data at rest and in transit. By analyzing user behavior patterns, AI can detect suspicious activities and enforce access controls, reducing the risk of unauthorized data breaches.
The future of artificial intelligence in data preservation and business records management holds immense promise for businesses seeking to thrive in a data-driven world. AI’s capabilities, such as data preservation, enhanced data classification, intelligent retention policies, predictive analytics, automation, and improved data privacy and security, offer significant efficiency, compliance, and strategic decision-making advantages. As AI technology advances, businesses must embrace these transformative solutions to stay ahead in the competitive landscape. By leveraging AI’s potential, enterprises can unlock new possibilities for data preservation and records management, setting the stage for a more intelligent and prosperous future.
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Archiving vs. Backup: Which Do You Really Need for Compliance?

Archiving vs. Backup: Which Do You Really Need for Compliance?

Everyone who has worked in records management has seen it before: Organizations keeping their backup copies of production data “because it’s needed for compliance.” This, however, turns out to be a costly move…and one that does not really address data retention needs. What is really needed for data retention is a proper data archiving system.

Which prompts the question: What is the difference? Why is backup not suitable for compliance, and what is gained from investing in a true enterprise data archive?
Archiving vs. Backup: Two Different Missions
The short answer to the above is that archiving solutions and backup solutions were created with two different goals in mind:
  • Backup makes a copy of data (both active and inactive) so that, should that data become damaged, corrupted, or missing, it can be recovered quickly.
  • Archiving makes a copy of inactive or historical data so it can be stored in an unalterable, cost-effective way for legal or compliance reasons.
Backup is an important part of a business continuity plan. Should a piece of hardware fail, or a database become corrupted, it still will be possible to recover the necessary data to keep business operations going.
Maintaining a backup system can be costly, however. The data in the system needs to be updated often, and made easily recoverable, should a disaster happen. The space and cost required to do so can become quite large as an organization’s data grows.
Archiving stems from the realization that not all data an organization has is needed for daily operations—it is not production data. Examples include old forms, transaction records, old email communications, closed accounts, and other historical data. But while this data has no ongoing use, it has to be kept to comply with laws having to do with data retention.
It’s easy to see how the two might be confused—after all, both kinds of technology are, in essence, making a copy of the organization’s data.
But whenever you have two different goals or purposes for two different pieces of technology, you are going to have some important differences as well. If those differences are large enough, you won’t be able to simply swap one technology for the other. At least, not without some major problems.
First Major Difference: The Cost of Space
When a bit of data is stored, there is a cost associated with it. That’s true whether that data sits in the cloud, on an on-prem server, or on a tape drive in a closet somewhere.
Not all storage costs are equal. Take cloud providers like AWS, Microsoft (Azure), and Google, for example. These big players tier their storage offerings, basing the price on things like accessibility, security, and optimization for computations. “Hot storage” holds data that might be used day-to-day and needs to be optimized for computing, and so is relatively much more expensive. “Cool” or “cold” storage is for data that is rarely used, and so does not need to be optimized or accessed quickly. Thus, it tends to be cheaper—sometimes by half or more.
The same goes for on-prem storage. Some data needs to be readily accessible, and so located on a server that needs to be maintained and secured. There are many more options for data that does not need to be accessible, like historical data.
The longer an organization stays up and running, the greater its older, inactive historical data is in proportion to its active data. This is why archiving is important: It saves this inactive data in a much more cost-efficient way, freeing up the systems that traffic in active data (and freeing up storage budget).
Second Major Difference: Immutability
An important part of compliance with data retention laws is keeping the data in an unaltered, and unalterable, state. This is where the idea of immutable storage comes into play. Immutable storage, such as a WORM (write once, read many) datastore, cannot be altered, even by an administrator. The data is, in a sense, “frozen in time.”
This is important for legal purposes. If data is needed for any reason, it is important to show that it has been stored in a way that resists any sort of tampering or altering. In short, immutability is built into most data archiving solutions, because immutability is important for the very tasks for which archives were engineered. The same might not always be true for data backups.

Another benefit of immutability: It provides built-in protection against ransomware attacks.

An important part of compliance with data retention laws is keeping the data in an unaltered, and unalterable, state. This is where the idea of immutable storage comes into play. Immutable storage, such as a WORM (write once, read many) datastore, cannot be altered, even by an administrator. The data is, in a sense, “frozen in time.”
Third Major Difference: Logging and Tracking
Along with alterability comes the idea of logging or tracking who has accessed a particular bit of data. Having a log of who accessed which data, and when, leaves an important trail of breadcrumbs when it comes to audits, as well as data privacy incidents. Most backup systems do not need this level of logging and tracking—they usually carry just enough information to verify when backup or recovery has been run, and how successful it was. Archiving provides a much more granular level of detail.
Fourth Major Difference: Scheduled Destruction
Once data is no longer needed for compliance purposes, it should be destroyed. That way, it no longer takes up space, nor runs the risk of being compromised (which can be a data privacy issue).
Best-in-class archives, because they are focused on compliance needs, have such scheduled destruction built in. Backup systems usually do not, as that would be antithetical to their purpose of saving data. (At best, backup systems overwrite previous backups, and some let the user determine how many backup copies need to stay current.)
Archiving and Backup: Which Does Your Organization Need? (And How Do You Know?)
Really, most enterprise-sized organizations need both. Business continuity plans need to include solutions for backup.
But those solutions make for a very costly, and mostly inadequate, archiving solution for compliance purposes. Different technology is needed for this.
So, if your organization is discussing disaster recovery and prioritizing things like speed to get up and running again with your production data intact, it’s best to explore a backup solution.
But if, like the customers above, you are looking to retain records or other data for compliance purposes, invest in a data archive.
Barry Burke, storage guru and CTO of Dell EMC for years, has a great way of conceptualizing the difference between the two technologies, looking not at what is done, but what the intent behind the action is:
In explaining the word “archive” we came up with two separate Japanese words. One was “”katazukeru,” and the other was “shimau”…Both words mean “to put away,” but the motivation that drives this activity changes the word usage.

The first reason, katazukeru, is because the table is important; you need the table to be empty or less cluttered to use it for something else, perhaps play a card game, work on arts and crafts, or pay your bills.

The second reason, shimau, is because the plates are important; perhaps they are your best tableware, used only for holidays or special occasions, and you don’t want to risk having them broken.
If plates are data and the table is your production storage system, then backup is shimau: The data is important to save, even at a high cost. Archiving is katazukeru: It’s the system itself that must be cleared so you can get on with the next activity…but, of course, you still want and need to save the plates.

Interested in what an archiving solution can do for your organization above and beyond backup? Take a look at our Omni Archive Manager, or reach out to talk to one of our specialists.

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Unveiling the Transformation: The Impact of Cloud Computing on Data Archiving

Infobelt

In today’s digital age, data has become the lifeblood of businesses worldwide. Every click, transaction, and interaction generate valuable information that fuels decision-making processes and drives organizational growth. However, with the exponential growth of data comes the pressing need for effective data management strategies, particularly in archiving. Traditional data archiving methods, reliant on physical storage solutions, must be revised to handle modern data’s sheer volume and complexity.
Enter cloud computing – a revolutionary technology transforming how businesses store, manage, and access data. By leveraging the power of the cloud, organizations can overcome the limitations of traditional archiving methods and unlock a myriad of benefits. In this blog post, we’ll delve into the profound impact of cloud computing on data archiving and explore how businesses can harness its potential to drive efficiency, scalability, and innovation.
The Evolution of Data Archiving
Before delving into the specifics of cloud-based data archiving, it’s crucial to understand the evolution of data archiving practices. Traditional data archiving methods typically involve storing data on physical hardware such as tape drives, hard disk drives, or optical media. While these methods served their purpose in the past, they are beset by limitations such as scalability constraints, high maintenance costs, and susceptibility to hardware failures.
Moreover, traditional archiving solutions often need help to keep pace with the ever-increasing volume of data generated by modern businesses. As data continues to grow exponentially, organizations are faced with the daunting challenge of finding cost-effective and scalable solutions to manage their archival needs.
The Rise of Cloud-Based Archiving
Cloud computing has emerged as a game-changer in data archiving, offering a host of advantages over traditional methods. At its core, cloud-based archiving involves storing data in off-site data centers managed by third-party providers. This approach eliminates the need for organizations to invest in and maintain their hardware infrastructure, thereby reducing capital expenditures and operational overhead.
One of the primary benefits of cloud-based archiving is scalability. Unlike traditional solutions, which require organizations to purchase additional hardware as their storage needs grow, cloud-based archiving allows businesses to scale their storage capacity on demand. This scalability ensures organizations can effectively manage their archival needs without hardware limitations.
Furthermore, cloud-based archiving offers improved accessibility and flexibility. With data stored in the cloud, employees can access archived information from anywhere, anytime, using any internet-enabled device. This enhanced accessibility facilitates collaboration and empowers employees to make informed decisions based on timely access to archival data.
Enhanced Data Security and Compliance
In addition to scalability and accessibility, cloud-based archiving offers enhanced data security and compliance features. Leading cloud providers implement robust security measures to protect archived data from unauthorized access, data breaches, and other security threats. These measures may include encryption, access controls, and multi-factor authentication.
Moreover, cloud providers often adhere to stringent compliance standards and regulations, such as GDPR, HIPAA, and SOC 2, to ensure that archived data meets legal and regulatory requirements. By leveraging cloud-based archiving solutions, organizations can streamline compliance efforts and mitigate the risk of non-compliance-related penalties and fines.
Cost-efficiency and Resource Optimization
From a financial perspective, cloud-based archiving offers significant cost savings compared to traditional methods. Organizations can eliminate upfront hardware costs and reduce ongoing maintenance expenses by outsourcing archival storage to cloud providers. Additionally, the pay-as-you-go pricing model employed by many cloud providers allows organizations to pay only for the storage they use, thereby avoiding costly hardware upgrades and over-provisioning.
Furthermore, by offloading archival storage to the cloud, organizations can free up valuable IT resources and personnel to focus on more strategic initiatives. Rather than spending time and effort managing hardware infrastructure, IT teams can allocate their resources toward innovation, development, and other high-value activities that drive business growth.
Leveraging Advanced Analytics and Machine Learning
Cloud-based archiving opens the door to advanced analytics and machine-learning capabilities that can unlock valuable insights from archived data. By harnessing the vast computational power of the cloud, organizations can analyze archived data to identify trends, patterns, and correlations that can inform strategic decision-making.
For example, businesses can use machine learning algorithms to analyze customer purchase history data archived in the cloud to identify upsell and cross-sell opportunities. Similarly, organizations can leverage predictive analytics to forecast future trends and anticipate customer demands based on historical data stored in the cloud.
Conclusion
In conclusion, the impact of cloud computing on data archiving cannot be overstated. By migrating archival storage to the cloud, organizations can achieve unparalleled scalability, accessibility, security, and cost-efficiency. Moreover, cloud-based archiving opens the door to advanced analytics and machine-learning capabilities that can unlock valuable insights and drive innovation.
As businesses grapple with the challenges of managing ever-growing volumes of data, cloud-based archiving represents a compelling solution that offers tangible benefits. By embracing cloud computing, organizations can future-proof their archival strategies and position themselves for success in an increasingly data-driven world.
By: Dusty Gilvin, COO & CRO, Infobelt

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The Role of PeopleSoft Archiving in Compliance and Data Security

Infobelt

In the high-stakes world of mergers and acquisitions (M&A), data preservation is crucial yet often underappreciated. As companies strive to merge their operations, cultures, and assets, the seamless and secure transfer of information is essential. This comprehensive analysis delves into why effective data preservation is not just a technical necessity but a strategic imperative that can dictate the success or failure of M&A endeavors.
Understanding the Importance of Data in M&A
Mergers and acquisitions involve combining the strengths of two (or more) companies to create a unified entity that is more competitive and profitable. In this context, data includes not just financial records and customer databases but also intellectual property, employee information, operational processes, and more. Each dataset plays a pivotal role in ensuring that the newly formed company can operate effectively from Day One.
Preserving this data involves much more than preventing loss. It includes ensuring data integrity, maintaining privacy and compliance with regulatory standards, and securing seamless access for decision-makers. Strategic data handling can accelerate integration, enhance value creation, and reduce the risk of costly legal and compliance issues.
Strategic Planning for Data Integration
The first step in preserving data during an M&A transaction is strategic planning. This involves identifying what data needs to be preserved, understanding its relevance to the merged entities, and determining how it will be integrated into the new business structure. Effective planning must address the following:
  • Data Mapping: Establishing an inventory of data assets from both companies.
  • Compliance and Privacy Concerns: Adhering to GDPR, HIPAA, or other relevant regulations.
  • Risk Assessment: Identifying and mitigating potential security risks.
  • Integration Framework: Outlining how data will be merged or migrated.
Strategic planning ensures that data management is proactive rather than reactive, preventing integration delays and potential conflicts post-merger.
Technical Challenges in Data Preservation
M&A activities pose unique technical challenges for data preservation, primarily due to the different systems and technologies employed by the merging entities. These challenges include:
  • System Compatibility: Ensuring that legacy systems and new technologies work harmoniously.
  • Data Structure Differences: Reconciling differing data formats and structures.
  • Volume and Complexity: Managing the sheer scale of data, especially in large mergers.
Overcoming these challenges requires robust technical strategies, often involving specialized software tools for data integration, quality management, and continuous data governance.
Legal and Regulatory Compliance
Data preservation must also address the legal and compliance aspects critically magnified during M&As. Regulatory frameworks such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the U.S. stipulate strict data privacy and security guidelines.
Companies must ensure that their data preservation strategies comply with these laws to avoid penalties. This involves:
  • Conducting Due Diligence: Assessing the data protection policies of the acquisition target.
  • Implementing Data Governance: Establishing policies that align with legal standards.
  • Securing Data Transfers: Using encrypted formats and secure channels.
The Role of Technology in Data Preservation
Advancements in technology play a pivotal role in facilitating efficient data preservation in M&A scenarios. Tools such as cloud storage solutions, enterprise resource planning (ERP) systems, and data integration platforms are indispensable. These technologies offer:
  • Scalability: To handle increasing volumes of data.
  • Flexibility: To adapt to the evolving needs of the merged entity.
  • Security Features: Protect data against breaches and unauthorized access.
Incorporating modern technology solutions streamlines the preservation process and provides a strategic advantage by enabling data-driven decision-making and innovation post-merger.
Case Studies and Best Practices
Learning from past mergers can provide valuable insights into effective data preservation strategies. Successful companies often employ best practices such as:
  • Early Involvement of IT Teams: Integrating IT teams from both companies early to align strategies and tools.
  • Regular Audits and Updates: Continuously assess the data preservation strategy for gaps and make necessary adjustments.
  • Employee Training: Educating staff on new systems and protocols to ensure smooth data handling.
Conclusion
Data preservation is a multifaceted and deeply impactful role in mergers and acquisitions. It requires careful planning, sophisticated technical solutions, and stringent compliance measures. By prioritizing data preservation, companies can facilitate a smoother merger process and lay the groundwork for a successful future.
Organizations that overlook the importance of data during M&A risk delays, legal penalties, and operational inefficiencies. Conversely, those who implement a robust data preservation strategy are well-placed to realize the full potential of their investment, underscoring the vital role that data plays in the modern corporate landscape.
By: Dusty Gilvin, COO & CRO, Infobelt

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The Relationship Between Data Governance and Application Retirement: A Strategic Overview

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In the rapidly evolving digital landscape, managing enterprise data through disciplined governance practices is crucial for sustaining business integrity and achieving compliance with increasing regulatory demands. Equally important is the strategic retirement of outdated applications, a process that streamlines IT operations and significantly enhances data security and operational efficiency. The intersection of data governance and application retirement is critical for organizations to drive substantial value, reduce risks, and optimize resources. This blog explores the relationship between data governance and application retirement, highlighting the benefits of integrating these disciplines.
Understanding Data Governance
Data governance refers to the overall management of the availability, usability, integrity, and security of an organization’s data. It involves setting policies and procedures that ensure data is managed properly and used correctly across the business. Effective data governance ensures that data is accurate, available, and secure and that it meets the standards set by both the company and regulatory bodies.
The Role of Application Retirement in Modern Businesses
Application retirement is phasing out legacy applications that are no longer needed or cost-effective. This process helps organizations reduce IT clutter, minimize security vulnerabilities, save on costs associated with maintaining outdated software, and redirect resources towards more value-generating activities.
Strategic Connection Between Data Governance and Application Retirement
Integrating data governance with application retirement can create a symbiotic relationship that enhances both processes. Below are key ways in which these two areas are interconnected:
  1. Ensuring Data Integrity and Security When an application is retired, data from that application often needs to be migrated to other systems or archived. Data governance plays a crucial role in this phase by ensuring that data is handled in a way that maintains its integrity and security. Governance policies dictate how data should be securely transferred, who has access to it, and how it should be used, preventing data breaches and loss during retirement.
  2. Compliance with Regulatory Standards Data governance frameworks ensure an organization’s data management practices comply with relevant laws and regulations. When an application containing sensitive or critical business data is retired, these governance policies ensure that all regulatory requirements are met during decommissioning, such as maintaining data privacy and proper archival methods.
  3. Minimizing Risk Decommissioning legacy systems involves significant risks, including data loss and potential compliance violations. A robust data governance strategy includes risk management protocols that help identify and mitigate these risks during the application retirement process. This includes thorough risk assessments and contingency planning, essential for a smooth transition.
  4. Streamlining Data Management Application retirement often leads to a consolidation of IT systems and data repositories. Data governance frameworks facilitate this process by providing guidelines on data consolidation practices, which help maintain data quality and accessibility. This streamlined approach reduces IT complexity and enhances the efficiency of data usage across the organization.
  5. Enhancing Decision Making Effective data governance allows organizations to maintain reliable and consistent, high-quality data. When combined with application retirement, this high-quality data can be leveraged to make better-informed decisions about which applications to retire, when, and how. Data analytics can play a role here, offering insights into application usage patterns, cost analysis, and the potential impact of retirement decisions.
Best Practices for Integrating Data Governance with Application Retirement
To maximize the benefits of integrating data governance with application retirement, organizations should consider the following best practices:
  1. Develop a Holistic Strategy
    Organizations should develop a comprehensive strategy that outlines how data governance will support application retirement. This strategy should include detailed policies on data handling, compliance, risk management, and data quality.
  2. Involve Stakeholders Early
    Engage stakeholders from across the business early to ensure that all aspects of data governance and application retirement are covered. This includes IT, compliance, business units, and data security teams.
  3. Utilize Technology
    Implement technology solutions that can automate and facilitate the integration of data governance and application retirement processes. This may include data management software, security tools, and compliance monitoring systems.
  4. Continuous Monitoring and Improvement
    Review and update the governance and retirement processes regularly to adapt to new challenges, technologies, and regulatory changes. Continuous improvement will help maintain the strategies’ relevance and effectiveness.
Conclusion
Integrating data governance with application retirement is a technical necessity and a strategic imperative. Organizations can enhance their data integrity, streamline IT operations, ensure compliance, and mitigate risks by aligning these two crucial areas. As businesses navigate the complexities of the digital world, the relationship between data governance and application retirement will undoubtedly become a cornerstone of strategic IT management, driving more informed, efficient, and secure business practices.
By: Dusty Gilvin, COO & CRO, Infobelt

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The Impact of SAP Archiving on Business Performance and Efficiency

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In today’s data-driven world, efficient enterprise information management has become crucial for maintaining competitive advantage. As a leading enterprise resource planning (ERP) software, SAP handles enormous volumes of data daily. However, accumulating data can slow down the system, leading to decreased performance and increased operational costs. SAP archiving addresses this challenge by effectively managing the data lifecycle and optimizing system performance. This blog explores the impact of SAP archiving on business performance and efficiency, providing actionable insights for businesses aiming to leverage this technology.
Understanding SAP Archiving
SAP archiving moves historical data from your active database to a separate storage location. This practice is essential for maintaining system efficiency and Compliance with data retention laws. Archived data is still accessible if needed, but it no longer burdens the core SAP database, thus enhancing system performance and reducing storage costs.
Why is SAP Archiving Important?
As SAP systems age, they accumulate data that can clog the database and adversely affect the performance. Archiving this data helps in several ways:
  • Improves System Performance: By removing old data from the database, you reduce the volume of data the system needs to process during routine operations, thereby speeding up access times and improving user satisfaction.
  • Reduces Costs: Storage costs are significantly lowered as archived data can be stored on less expensive media.
  • Ensures Compliance: Many industries have strict data retention and deletion regulations. SAP archiving helps meet these legal requirements without compromising system performance.
  • Enhances Data Management: With better data lifecycle management, companies can focus on analyzing current and relevant data, improving decision-making processes.
Impact on Business Performance and Efficiency
Implementing SAP archiving can transform business operations. Below, we explore several benefits that directly impact performance and efficiency.
  1. Enhanced System Performance
    A primary benefit of SAP archiving is the improved performance of the SAP database. As the volume of data in the live system is reduced, the time it takes to execute queries and generate reports decreases significantly. This leads to faster transaction times and boosts overall system responsiveness, enhancing user productivity and satisfaction.
  2. Cost Reduction
    Data storage costs can escalate quickly for enterprises that do not practice data archiving. By archiving older data, companies can move less frequently accessed data to cheaper, slower storage solutions. This approach reduces the immediate financial burden and optimizes investments in IT infrastructure.
  3. Compliance and Risk Management
    Compliance with data retention laws is critical for businesses in regulated industries. SAP archiving facilitates Compliance by securely storing data for the required retention periods and providing tools to ensure that data can be deleted when it is legally permissible. This reduces the risk of compliance violations, which can lead to hefty fines and reputational damage.
  4. Improved Data Accessibility and Management
    While it might seem counterintuitive, archiving can improve data accessibility. Decluttering the central database makes the remaining data more relevant and easier to manage. Archiving solutions often come with sophisticated indexing and search capabilities, making retrieving needed information from the archive easier.
  5. Scalability and Future-Proofing
    As businesses grow, so does the data they generate. SAP archiving allows scalable data management strategies that accommodate growth without compromising system performance. This scalability ensures the SAP system remains robust and responsive, supporting business expansion and innovation.
  6. Environmental Impact
    Reducing the physical storage and energy consumption required to maintain large volumes of data not only cuts costs but also aligns with sustainable business practices. This aspect is increasingly important as companies move towards greener operations.
Best Practices for SAP Archiving
To maximize the benefits of SAP archiving, consider the following best practices:
  • Regular Audits and Reviews: Regularly audit your data and archiving processes to meet business needs and compliance requirements.
  • Define Archiving Rules: Clearly define what data should be archived, considering factors like age, business relevance, and legal requirements.
  • Ensure Data Integrity and Security: Implement robust security measures to protect archived data and ensure data integrity during archiving.
  • User Training: Educate users about the benefits and processes of SAP archiving to ensure smooth implementation and utilization.
Conclusion
SAP archiving is a powerful tool for enhancing business performance and operational efficiency. By managing the data lifecycle more effectively, businesses can improve system performance, reduce costs, ensure Compliance, and prepare for future growth. As more companies recognize the benefits of this practice, SAP archiving is becoming an essential component of effective data management strategies in the digital age. Implementing it with best practices in mind ensures that businesses reap all the potential benefits, turning data management from a challenge into a strategic asset.
By: Dusty Gilvin, COO & CRO, Infobelt

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The Impact of Cloud Computing on Data Archiving: A Comprehensive Analysis

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In the digital age, the importance of data storage and management cannot be overstated. As organizations generate massive volumes of data, traditional data archiving methods have increasingly shown scalability, cost, and security limitations. Enter cloud computing—a revolutionary technology transforming data archiving strategies across industries. This article delves into how cloud computing has redefined data archiving, offering enhanced efficiency, security, and accessibility.

Understanding Cloud Computing and Data Archiving
Before assessing the impact of cloud computing on data archiving, it is crucial to understand the basics of both concepts. Cloud computing refers to delivering computing services—including servers, storage, databases, networking, software, and analytics—over the Internet (“the cloud”). This model offers flexible resources, faster innovation, and economies of scale. On the other hand, data archiving involves moving older, less frequently accessed data to a separate storage device for long-term retention. Archived data is preserved securely and economically while maintaining accessibility for compliance, governance, or historical reference.
Enhanced Accessibility and Scalability
One of the primary advantages of using cloud-based solutions for data archiving is enhanced accessibility. Cloud services allow data to be accessed from any location at any time, as long as an internet connection exists. This global accessibility ensures that businesses can operate remotely and stakeholders can reach data regardless of geographical location.
Moreover, cloud computing offers unparalleled scalability compared to traditional data archiving methods. Conventional data storage solutions require physical hardware expansions to accommodate more data, which can be costly and time-consuming. In contrast, cloud services provide dynamic scalability—businesses can increase or decrease their storage capacity with minimal lead time, adapting quickly to changes in data archiving needs.
Cost Efficiency
Cost efficiency is another significant impact of cloud computing on data archiving. Traditional archiving solutions involve initial hardware and software costs and require ongoing maintenance, power, and cooling expenses. Cloud-based archiving solutions, however, typically operate on a pay-as-you-go basis, where businesses only pay for the storage they use without the need for upfront capital investment. This model can lead to substantial cost savings, especially for organizations that need to scale their storage needs based on fluctuating data volumes.
Improved Data Security and Compliance
Given the rising number of cyber threats, data security is a top priority for organizations. Cloud providers invest heavily in security technologies and protocols to protect data. These include physical security measures, encryption methods, and multi-factor authentication processes that are often more sophisticated than those implemented in on-premise data centers.
In addition to security, compliance with regulatory requirements is a critical consideration for data archiving. Cloud providers are adept at adhering to various international and local regulations, such as GDPR in Europe and HIPAA in the United States. By leveraging cloud services, organizations can ensure that their data archiving practices comply with the legal frameworks, reducing the risk of costly penalties.
Enhanced Disaster Recovery
Cloud computing also enhances disaster recovery capabilities in data archiving. Traditional data recovery methods are often slow and can result in significant data loss. Cloud-based archiving solutions offer robust disaster recovery plans that ensure data is replicated in multiple locations, safeguarding against data loss due to physical disasters, system failures, or cyber-attacks. This redundancy allows businesses to resume operations quickly after a disaster, minimizing downtime and associated losses.
Automation and Innovation
Adopting cloud computing in data archiving also opens doors to automation and innovative practices. Many cloud services incorporate machine learning and artificial intelligence to automate data backup, security monitoring, and compliance checks. This automation reduces the burden on IT staff and enhances the accuracy and efficiency of data archiving processes.
Furthermore, cloud computing enables advanced analytics on archived data. Businesses can utilize cloud-based tools to analyze historical data for insights that inform strategic decisions. This capability transforms data archives from static data repositories into dynamic assets that can drive business growth and innovation.
Challenges and Considerations
Despite its benefits, cloud computing in data archiving is challenging. Concerns over data sovereignty, particularly regarding where data is physically stored and how it is accessed, continue to pose issues for specific organizations. Additionally, the dependence on internet connectivity means that any connectivity issues can disrupt access to archived data.
Organizations must also carefully select their cloud provider and understand the service level agreements (SLAs) in place. The choice of provider can significantly impact the cost, efficiency, and security of data archiving solutions.
Conclusion
Cloud computing has undoubtedly transformed the landscape of data archiving, providing numerous benefits such as enhanced accessibility, scalability, cost efficiency, security, and disaster recovery. As technology evolves, it is anticipated that more organizations will embrace cloud-based archiving solutions, leveraging the latest innovations to enhance their data management strategies.
However, businesses must carefully navigate the complexities and challenges associated with cloud data archiving. By doing so, they can harness the full potential of cloud technologies to secure and optimize their archival processes, ensuring that they not only keep pace with current demands but are also well-prepared for future challenges.
By: Dusty Gilvin, COO & CRO, Infobelt

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The Future of Email Archiving- Trends and Predictions for the Next Decade

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As businesses navigate the digital transformation era, email remains a fundamental communication tool despite the proliferation of instant messaging and collaboration platforms. The immense volume of data generated through email communications necessitates effective archiving solutions to enhance operational efficiency and comply with legal and regulatory standards. Looking ahead, the future of email archiving is poised to be shaped by several significant trends and technological innovations. This blog explores the upcoming trends and predictions for email archiving over the next decade, providing insights into what businesses might expect and how they can prepare.
The Growing Importance of Email Archiving
Email archiving involves storing emails in a way that makes them easily retrievable and secure, ensuring that businesses can access historical communications for purposes such as compliance auditing, legal discovery, and business analysis. With the increasing scrutiny of data privacy and the rising incidences of cyber threats, the role of email archiving is becoming more critical than ever. Organizations are not only looking to preserve emails but are also focused on harnessing sophisticated tools to enhance the security and usability of stored data.
Predictions for Email Archiving in the Next Decade
  1. Integration of AI and Machine Learning
    Artificial intelligence (AI) and machine learning (ML) are set to revolutionize email archiving by automating complex processes and improving the accuracy of data retrieval. AI can help categorize and tag emails more effectively, facilitating quicker searches and more organized archives. Moreover, ML algorithms can identify patterns in email data, aiding in anomaly detection, which can be crucial for early spotting data breaches and security threats.
  2. Enhanced Security Features
    As cyber threats evolve, so must the security measures within email archiving systems. Future email archiving solutions will likely incorporate more advanced encryption technologies, multi-factor authentication, and better access controls. These features will help protect archived data from unauthorized access and potential breaches, providing businesses with higher security assurance.
  3. Increased Adoption of Cloud-Based Solutions
    The shift towards cloud-based email archiving solutions is expected to accelerate. Cloud storage offers scalability, flexibility, and cost-effectiveness that traditional on-premises solutions need help to match. Cloud providers typically ensure data is stored across multiple geographically dispersed data centers, offering better disaster recovery capabilities. As cloud technology advances, more organizations will migrate their email archives to the cloud to benefit from these advantages.
  4. Regulatory Compliance and E-Discovery
    Regulatory compliance will drive innovation in email archiving technologies. As governments worldwide tighten data protection laws, email archiving solutions must be adaptable to various legal frameworks. This adaptability includes features that support e-discovery, such as sophisticated search capabilities and robust audit trails, which help organizations respond quickly to legal requests for information.
  5. Predictive Analytics and Data Insights
    Future email archiving systems will store emails and provide predictive analytics to derive actionable insights from the archived data. These systems will help businesses anticipate trends, manage risks, and make informed decisions based on historical email data. The analytics integration will transform email archives from static data repositories into dynamic tools that actively support business strategy.
  6. Automation of Retention Policies and Lifecycles
    Automating retention policies and the lifecycle management of emails will become a standard feature in future archiving solutions. Automation will ensure that emails are retained for the exact duration required by law or company policy and are then securely disposed of, reducing the risk of data hoarding and non-compliance.
  7. User-friendly Interfaces and Seamless Integration
    As the workforce becomes more technologically savvy, there will be a higher demand for email archiving solutions that offer user-friendly interfaces and seamless integration with other business systems. Future solutions must be more intuitive and integrated, providing users with a seamless experience and reducing the learning curve of new software deployments.
Conclusion
The future of email archiving is set to be dynamic and heavily influenced by technological advancements, regulatory changes, and evolving business needs. By staying informed of these trends, organizations can ensure they are well-prepared to handle the challenges and opportunities that lie ahead in email management. Investing in advanced email archiving solutions will help businesses comply with legal requirements and enhance operational efficiency, improve data security, and unlock valuable insights from their email data. As we move into the next decade, the strategic importance of email archiving in business operations will undoubtedly continue to grow, becoming an essential tool in the digital arsenal of forward-thinking companies.
By: Dusty Gilvin, COO & CRO, Infobelt

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Rijil is responsible for overseeing the day-to-day operations of Infobelt India Pvt. Ltd. He has been integral in growing Infobelt’s development and QA teams. Rijil brings a unique set of skills to Infobelt with his keen understanding of IT development and process improvement expertise.

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Founder and Chief Delivery Officer

Kevin is a co-founder of Infobelt and leads our technology implementations. He has in-depth knowledge of regulatory compliance, servers, storage, and networks. Kevin has an extensive background in compliance solutions and risk management and is well versed in avoiding technical pitfalls for large enterprises.