Next-Gen Solutions and Strategies for Enhancing Data Quality and Analytics

It’s undoubtable that the adoption of cloud architectures has redefined the landscape of data and analytics. With an innumerable amount of technologies and solutions on the market today, knowing how to strategically implement these tools to best serve your enterprise is, arguably, a good problem to have—yet a problem nonetheless.

In a roundtable webinar hosted by DBTA, experts in data management and analytics joined to examine the best practices and tools for adapting to the needs of modern data while keeping in mind the needs of modern enterprises.

Rachel Pedreschi, VP technical services at Ahana, started the conversation by reviewing the optimal components of a data infrastructure. At its essence, it is a composition of users and data where users intend to commune with that data, wherever it's stored, to procure actionable insights. Through a collection of disks and SQL queries, Pedreschi presented  the well-known data warehouse.

The conversation led into a dissected analysis of where the layers of an enterprise’s data infrastructure can be improved to accommodate for performance and resource needs. Enhancements like S3 storage, open source tools, AWS Glue or Hive Metastore, and Presto for SQL queries transforms the age-old data warehouse into an open SQL data lakehouse.

While this transformation may seem like an arduous task, Ahana Cloud for Presto is available for alleviating transition pains. Putting all of these improvements into a single, easily-managed UI, the solution brings customers from zero to open data lakehouse in 30 minutes. Ahana Cloud for Presto is built for data teams of all experience levels, offering a moderate level of control deployment without taking data out of your own systems. As an in-memory distributed solution, Ahana Cloud for Presto is as fast as it is streamlined.

According to Traci Curran, director of product marketing at Actian, data is hard! Accompanying modernity is complexity; modern data infrastructures require a myriad of steps and layers to successfully transform raw data to actionable data. Enterprises must develop practices—such as those that increase customer attainment and retainment, optimize and streamline operations, and empower faster analytics—to adjust to the needs of modern data.

“Actian has decided to embrace, what we call, a cloud data platform,” said Curran. “We’ve taken the best-of-breed of all of our technologies and moved this into a cloud native platform. We want to allow analysts and data consumers to self-serve while enabling data experts to have some control over how that data is used throughout the business.”

The Avalanche Cloud Data Platform by Actian centers on native integration, empowering users to easily ingest data, transform it, and publish it onto a platform that can be utilized by whoever needs it. The platform offers features such as data integration visibility and orchestrations, BI and advanced analytics at 10x performance, improved resource productivity, and more.

Joey Jablonski, VP of analytics at Pythian, guided viewers toward a discussion of cultivating the best data platform that empowers its users to consume data, and do so effectively. Ultimately, the data estate is evolving; the transition to cloud architectures has initiated a need for self-service and democratization.

“As we go down the path of how to build data-enabling platforms that an organization can consume successfully, we start to look at the platform as the centralized ability to drive compliance, retention of data, and transformation policies, so both our producers and consumers of data are empowered to operate independently,” explained Jablonski.

Democratization of data increases the number of users that can access it; Pythian’s objective is to enable access without losing observability and control, according to Jablonksi. And in order to democratize, data must be easy to find, trustworthy, timely, and protected.

Drawing from Pythian’s ten best practices for building data platforms, Jablonski implored viewers to design the data platform for their specific data strategy. Metadata-driven processes is the next of Pythian’s tenets, encouraging metadata as the key towards meaningful governance and lower operational overhead. Finally, thinking early about data science will allow enterprises to have a stable foundation for their advanced capabilities and tools to thrive.

Concluding the roundtable, Vasu Sattenapalli, CEO of RightData, explored the particular needs of modern data as it exists as a product. Sattenapalli emphasized that the single-most critical modern need to accommodate is empowering business with the right data, at the right time, to the right stakeholders.

Current solutions only satisfy a small subset of modern data, explained Sattenapalli. With increasingly varied and differing tools on the market, enterprises need an intuitive experience designed for corporate data now more than ever.

Features such as self-service infrastructures, decentralized data ownership, integrated catalog and business descriptions, as well as bundled active and passive metadata are fundamental toward embracing data as a product. Similarly, observability, trust, and augmented data quality serve to enhance enterprise data.

RightData’s tools, the Dextrus platform and RDt software, combine to simplify enterprise data modernization journeys with holistic data management capabilities. The former provides a modern workflow for data integration and machine learning, while the latter ensures data observability, testing data at every stage for improved overall quality.

“RightData tool sets are targeted to provide a unified experience to data stakeholders by providing data management tools under one roof,” said Sattenapalli.

For an in-depth discussion about modern data and analytics strategies, you can view an  archived version of the webinar here.