Why Data Sharing is the Key to Evolved Distribution Processes

May 04, 2022 - 4 minutes to read

3 Ways The Modern Data Company Thinks Differently About Data

E. Wallace By E. Wallace

We, at the Modern Data Company (Modern), still cringe no matter how many times we hear statistics about how long data scientists spend cleaning data for use or how much data goes to waste restricted in silos. Data is a company’s lifeblood — beyond the “new gold” or “the new oil,” data is like a living thing that should remain in motion to support real-time, data-driven decision-making.

That’s why Modern created DataOS. Companies need a different approach to their data challenges, and a data operating system like this offers the only opportunity to streamline and simplify data no matter the source or format –– including legacy systems. In fact, Modern thinks about data differently from other data solution companies. Here are three things DataOS does differently:

Data ownership is a construct

In the old paradigm, data belonged to specific teams or administrators. Anyone seeking data had to jump through rigorous hoops to obtain permission to access data or initiate a query through IT. If even the smallest thing changed, users had to start over at the beginning of the queue, adding months to an already lengthy process.

Data ownership is a construct. In this construct, data doesn’t belong to the enterprise itself and must remain within its rigid silos. This model doesn’t lend itself well to a company working together on a comprehensive, collaborative data strategy.

So Modern turned the concept of data ownership on its head, moving the entire idea of ownership to the enterprise itself rather than team members. Now, all data comes under one single view, and administration sets tag-based access controls. These controls are applied to a single view across source systems, simplifying the implementation of security and ensuring that the rules are transparent and universally applied. This approach enables any user across the enterprise to access the entire data catalog compliantly through row and column level redactions, data abstraction, and data masking.

Now, teams can leverage data-driven decision-making in real-time.

Data pipelines should be accessible to everyone

“That’s wonderful,” companies might say, “but team members still need IT to build the appropriate pipelines and scrub data for use.” This is where DataOS really begins to shine. In addition to facilitating self-serve data for all stakeholders within a company, the operating system also reduces the need for technical expertise to run queries.

Modern takes a right-to-left approach. Users indicate what they need to happen with data, and the system builds the appropriate pipeline for them — no coding necessary. And all data remains visible and findable thanks to a simple search function that locates necessary data using a familiar, Google-like query approach.

Even more, a bird’s eye view of data offers visibility into who is using what data. This frees up IT from needing to work on a constant stream of data tasks from other departments but still provides transparency.

In addition, DataOS profiles all data and provides analysis on details such as cardinality, completeness, and other quality attributes. Finally, business-focused data validation rules help organizations objectively quantify their data quality for oversight purposes.

Data products should adapt to the organization, not vice versa

One of the biggest frustrations companies have is feeling locked into a product or service. Unfortunately, many data products and solutions require some measure of lock-in, whether it’s vendor-related or product-related. Whenever a company needs to adopt a new solution, integration challenges cause problems and delays.

Modern’s DataOS creates an operating layer, a connective tissue for data that mitigates common integration problems. It pulls data from any source and in any format, providing unprecedented visibility into what data assets the company actually has. It works with any existing vendor solution, whether it’s the newest release from a hot startup or a legacy system that is years old.

DataOS never requires companies to move their data to begin extracting value. Using a unique model, map, and load approach in place of traditional ELTs or ETLs, companies don’t need to worry about data loss uploading data into third-party storage. Even better, companies pay for use rather than taking on costly monthly subscriptions or upfront bulk costs.

Don’t just think about data differently — act differently

Companies can’t just purchase their way into a comprehensive, digitally-transformed data strategy. However, those purchases and investments don’t have to go to waste. DataOS can integrate all existing tools and create a data flow that finally allows organizations to make use of data, maximize the value of existing data tools, and build a secure governance strategy that never locks data in — vendor, tool, or storage.

It’s time to start thinking and acting differently where data is concerned. DataOS can transform how both business users and technical users approach data for business value. It creates a platform that users can leverage without special technical knowledge but offers robust tools for technical users to complete higher-order tasks. It is the culmination of everything Modern believes about data, and thanks to Modern’s unique take, companies can finally untangle business data for maximum value.

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