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What's Ahead in Data Management in 2023?

Data management is fundamental to every application. Managing this precious asset is an essential competency in modern businesses of every sort. Innovations in data platforms are being adopted, and data management approaches are evolving rapidly to keep pace. Increasingly, enterprises are converging their data warehouse, data lake, and other data management platforms onto distributed cloud-native infrastructures. As more types of data are consolidated into their platforms, enterprises implement more scalable DataOps pipelines and more comprehensive governance practices to manage it all.

Webinar Recording: Accelerating Cloud Data Modernization

As organizations seek to become more competitive, they are often looking to enrich their data sets for analytics to gain deeper insights. The data used for enrichment may include text data, machine data, image data, geospatial data, and real-time data. This data may be high volume, highly diverse, and disparate in nature. As part of this effort, organizations are moving to cloud data platforms to store and manage this modern data.

Webinar Recording: Powering Modern Applications: Data Management for Speed and Scale

Designed to be fast, scalable, flexible, and user-friendly, modern applications are at the center of the innovation and automation that is transforming companies, industries, and society today. At the same time, modern applications, increasingly built with microservices, also come with requirements that traditional data management approaches fall far short of effectively meeting.

Demo: Unravel Data - Keep Cloud Data Budgets on Track (Automatically)

Data teams need to be able to set cloud data budgets at a specific scope - and know if your various teams or departments are tracking to those budgets. But today, most data teams only know that the budget was overrun after it’s too late. With Unravel, establishing and tracking budgets to prevent overruns is easy.

Webinar: Unlocking the Value of Cloud Data and Analytics

From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data.

Demo: Unravel Data - Code-Level Insights for DataOps Teams

To ensure that jobs are running optimally, DataOps teams need to look at the detailed code. But DataOps teams don’t have the right tools to easily examine problematic code - or a simple path to optimizing it. With Unravel Data, DataOps teams can quickly troubleshoot applications that are throwing errors - all the way down to a specific line of problematic code. All in a single view.