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 In today’s data-driven world, The Ultimate Guide to Legacy Data Management highlights a transformative truth: legacy data is more than a regulatory requirement or storage concern—it is a strategic asset that can unlock business intelligence, drive insights, and inform long-term decision-making . Enterprises that consolidate, govern, and analyze historical data gain a competitive advantage, turning decades of accumulated information into actionable intelligence. Legacy data often sits idle in retired systems, unstructured archives, or silos, overlooked and underutilized. However, by leveraging modern data platforms, enterprises can extract valuable trends, perform predictive analytics, and generate insights that drive growth, operational efficiency, and customer understanding. Why Legacy Data Holds Strategic Value 1. Historical Insights Enable Smarter Decisions Decades of enterprise data reveal: Long-term customer behavior patterns Market cycles and trends Product per...

  Generative AI is revolutionizing the life sciences industry , enabling faster insights and innovation across clinical trials, drug discovery, and healthcare analytics . However, without proper data governance , enterprises risk non-compliance, privacy breaches, and unreliable results. By combining generative AI with robust governance , organizations can safely harness AI’s potential while adhering to global regulations.   Enterprise AI for Life Sciences Innovation Optimizing Clinical Trials with AI Clinical trials are complex, expensive, and time-consuming. AI can streamline trial processes and optimize outcomes: Predictive analytics identify the right patient populations AI models optimize trial design and resource allocation Real-time insights improve decision-making and reduce delays Integrating AI in trials ensures efficiency, accuracy, and measurable results . Keywords: Clinical trials AI optimization, AI in pharmaceutical R&D Ensuring Compl...

  Enterprises today face increasing pressure to protect sensitive data while maintaining usability for analytics, development, and AI. Two primary techniques — data masking and encryption — each serve different purposes. Understanding when and how to use each is critical for minimizing risk, ensuring compliance, and maintaining operational efficiency.  Data Masking vs. Encryption: Which Shield Protects Against a $4.88M Breach? This article provides a decision framework to help organizations determine the right approach for each scenario. Understanding Data Masking vs Encryption Data Masking: Replaces sensitive data with fictitious, yet realistic, values Ideal for non-production environments like development, testing, or analytics Maintains data structure and referential integrity for functional workflows Encryption: Converts data into unreadable format using cryptographic keys Ensures data is protected at rest, in transit, or in storage Requires pro...

 Modern governments are undergoing a profound digital shift. As citizens expect faster services, higher transparency, and personalized engagement from public agencies, data has become the centerpiece of effective governance . Whether enabling real-time traffic insights or accelerating welfare approvals, smart data management transforms how governments serve people. However, many departments still struggle with legacy systems, fragmented databases, and manual workflows — slowing down service delivery, increasing fraud risk, and limiting transparency. To overcome this, forward-thinking agencies are embracing platforms like SOLIXCloud Common Data Platform (CDP) to unify, govern, and activate their data for improved public outcomes. Why Smart Data Management Matters for Government Agencies 1. Citizen Expectations Are Higher Than Ever People now expect government portals to work like online banking or e-commerce apps: Fast Transparent Accessible Personalized Without...

  Introduction Enterprise IT teams face increasing pressure to manage rising data volumes, legacy systems, and compliance requirements. This makes application retirement a critical element of modern IT strategy. The Solix Application Retirement Solution stands out by offering a complete, end-to-end approach that simplifies the retirement process while ensuring secure, long-term access to legacy data.  how the solix application retirement solution leads the way What Makes Solix Different? A Complete Retirement Framework Most organizations still take an ad-hoc approach to application decommissioning — manually exporting data, shutting down servers, and hoping compliance standards are met. This leads to data loss, audit failures, and long-term risk. Solix eliminates these challenges with a built-in, structured, repeatable framework , ensuring: No data is lost All compliance needs are met Historical information remains accessible Decommissioning becomes fast, pre...

 Enterprises today face mounting pressure to manage data growth, meet strict regulatory mandates, and retire legacy systems effectively. Many organizations long relied on IBM’s InfoSphere Optim solutions for application-retirement archiving and structured data lifecycle management. However, with withdrawal of support, connectivity and access risks have escalated. The new datasheet from Solix outlines how they provide a seamless migration path enabling full access, governance and control of archived data.  Replace IBM Infosphere Optim with SOLIXCloud This article examines: The risks posed by continuing with IBM InfoSphere Optim, Why Solix is a compelling alternative, Key benefits and migration considerations for enterprise archiving. The Risk of Staying with IBM InfoSphere Optim As outlined in the datasheet, IBM announced effective December 16, 2022 the withdrawal of marketing, entitlements and support for critical components of InfoSphere Optim—specifically the “Opt...

  Introduction: From Passive Storage to Intelligent Insight For decades, file archiving has been seen as a passive storage function—simply moving old or inactive data into low-cost storage to save space. However, as digital data volumes explode, this traditional approach has become unsustainable. Organizations are now sitting on vast amounts of dark data —unstructured files that contain valuable business insights but remain untapped. How Deep Neural Networks Are Redefining the Future of File Archiving Enter deep neural networks (DNNs) —the foundation of modern artificial intelligence. These powerful models are now redefining the very nature of file archiving by transforming it into a dynamic, intelligent layer that can understand, classify, and extract insights from data at scale.    What Are Deep Neural Networks—and Why They Matter in Archiving Deep neural networks mimic how the human brain processes information. They analyze data through multiple layers, learning ...

 For businesses using Salesforce as their CRM or customer-platform, the Salesforce Informatica acquisition brings both promise and complexity. It promises richer data-capabilities — but also compels customers to rethink their data strategy, especially around data governance, integration, quality and analytics. 1. Opportunities for Salesforce customers With Informatica under the Salesforce umbrella, existing Salesforce customers can expect tighter integration of data-catalog, data-governance and data-quality features. This means: unified customer records, improved data-trust, better analytics, and a smoother AI-journey. For example: “Unified customer data… real-time data integration across diverse sources.”  2. Challenges and risks to manage Despite opportunity, customers must watch for: Integration timelines (the deal is expected to close early FY 2027)  Changes in licensing, support or ecosystem partners Potential vendor-lock-in or diminished vendor-neutral...

 As organizations modernize their IT infrastructure, they often reach a critical decision point — whether to retire or decommission legacy applications. Both strategies aim to reduce operational overhead and improve agility, but they differ fundamentally in how they handle data . The success of either strategy depends on one central factor: how well your enterprise manages and archives data . Without a proper archiving plan, even a well-intentioned retirement or decommissioning project can expose you to compliance risk, data loss, or unnecessary costs. This article explores the best practices for enterprise data archiving when choosing between application retirement and application decommissioning. The Role of Data Archiving in Application Lifecycle Management Every application — whether operational or retired — produces valuable business data over time. As applications reach end-of-life, organizations must decide how to preserve, secure, and access that data in the future. ...