I am sure you have heard of data lakes and how much easier it is to have all of your data in one centralized location. While reading the hundredth white paper on modern data management systems, you've probably already asked: Why is the same paradigm — the data warehouse — repeated over and over?

Even if they all seem to do the same, what makes the difference between all the available data platforms? Starting with the Databricks Data Lake, to Hadoop, Snowflake, or Oracle, they all promise to offer better ways to manage data. But a fundamental problem remains unsolved across all variants mentioned.

Which problem? Data silos continue to persist in modern data infrastructures, complicating data governance, foster AI bias and limiting flexibility. You've likely wondered why no one has effectively solved it.

The fact that you are here shows you care about avoiding data silos and moving toward better solutions. Let's take this journey together to uncover how a modern data management system, like Scalytics Connect, can solve these challenges in a future-oriented way.

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Data, Networks, and Firewalls

To handle the massive amounts of data across diverse origins, software companies have developed enterprise data management platforms that run on hybrid data infrastructures. Such infrastructures combine on-premise systems with cloud environments. These systems promise a comprehensive data pipeline, but the real challenge lies in data governance and regulatory compliance.

Scalytics Connect offers a unique solution for training AI systems and developing digital twins with real company data, providing unparalleled support in these areas. – Mirko Kämpf. co-founder & chief strategist

Short: Scalytics gets you back in the driver's seat by taking the risk out of overboarding ETL processes, which often grow over time and end up with uncontrollable copies.

One significant challenge is the lack of data mobility across regions due to regulatory restrictions. Traditional ETL systems may support compliance, but they require significant additional work and may lead to data lock-in. Scalytics Connect, on the other hand, is a data sovereignty solution that avoids this problem by bringing algorithms to the data rather than the other way around. This approach ensures compliance with regulations like the GDPR while minimizing the need for moving data.

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Ready for AI?

We often hear that data integration is the top priority for organizations aiming to become AI-ready, but what does this mean in practice? An (sponsored) MIT study on key investment areas for executives found that data pipelines and data governance are critical for ensuring AI success.

But is that really the case? Is data mobility really the only solution to this puzzle? We clearly disagree at this point: It's not the mobility of the data, i.e. moving and copying through the endless ETL and ELT pipelines. Rather, we see the key to successful data use in the ability to work reliably on any data with algorithms - whether analysis (BI) or AI training. All of this under the additional condition that only the relevant information is used in the secure context of its use, which means that the data governance context is always maintained. The data itself is therefore never removed from this secure data governance context.

At Scalytics Connect, we take a different approach: it's not about moving data, but about real-time data processing where the algorithms are brought to the data. This shift makes AI-readiness possible without the complexities of ETL pipelines and data lakes. AI-enabling data frameworks like Scalytics Connect make it more reachable for companies to train and fine-tune their own AI models while maintaining strict data governance protocols.

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The Firewall and Data Sovereignty

Many, I tend to say all, organizations are concerned about data moving beyond the corporate firewall. Data sovereignty is crucial, especially for those working in regulated industries. Regulations like the GDPR prohibit transferring data out of its jurisdiction, and for many, this means their data must remain behind a firewall, in a secured space.

Scalytics Connect ensures data doesn't leave its original environment by positioning and executing algorithms decentrally. Our solution not only maintains data sovereignty but also provides end-to-end control and security through a robust data governance data framework. With AI fabric technologies like Scalytics Connect, businesses can leverage real-time data analytics and AI while avoiding the risks associated with data movement.

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Summary

Despite the promise of data lakes, data silos persist in modern data infrastructures. Scalytics Connect offers a solution by bringing algorithms to data, avoiding data movement and ensuring data sovereignty. This approach enables AI-readiness without the complexities of ETL pipelines and data lakes. Read our second part of this small series to understand how and why!

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TL:DR:

Traditional data management approaches often rely on centralized models like data lakes and warehouses, which involve moving and copying data across various systems. However, these methods introduce significant risks, especially concerning data privacy, compliance, and control. Scalytics Connect addresses these challenges by offering a new approach to data management—one that avoids the pitfalls of data mobility and focuses on decentralized data processing.

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