Central to any modernization strategy is data management, acting as the true foundation for any advanced technology to succeed and thrive. As scalability, flexibility, and cost effectiveness continues to dictate key goals for data management strategies, the migration to the cloud is the vehicle by which enterprises transform into agile, data-driven entities.
In DBTA’s latest webinar, Modernizing Your Data and Analytics in the Cloud, experts examined key trends and best practices for extracting the most value from data and the cloud to drive positive, modern business outcomes.
While the cloud is a desirable goal, it’s not without its challenges. For instance, analyzing JSON formats remains a difficult task due to its semi-structured, dynamic nature, noted Jeff Morris, vice president of product and solutions marketing at Couchbase.
Developers often flock to JSON for its flexibility boons, yet this format’s agile nature means that “it’s very difficult to get [it] into an organizational structure [that] you’re familiar with in an analytic universe,” said Morris. The analytical advantage, if achieved, comes from JSON’s ability to capture metadata and metrics, enriching data and downstream activities. Morris further pointed to JSON as being critical in the era of AI, able to store prompt variables, provide validation of full-prompt conversations, and more, serving as the data format for AI.
To tap into JSON’s true value, Couchbase offers Capella Columnar, the Couchbase cloud database-as-a-service (DBaaS) that brings the power of NoSQL to the world of analytics. Eliminating the need for complex transformations to prepare JSON for analytics, Capella Columnar delivers zero ETL by unifying operational and analytical data stores into a single platform.
For any modernization initiative, “there are multiple variables that we have to consider when we are trying to maximize the opportunity of what data can do for the enterprise,” said Catalina Herrera, field CDO at Dataiku.
From analytics to generative AI (GenAI), Dataiku recognizes modernization as a multi-variable problem, delivering a universal AI platform that acknowledges each component necessary to drive positive data outcomes. The Dataiku platform transforms AI from risk to true opportunity, uniting people, data, governance, and technological optionality with:
- A people strategy that allows everyone to collaborate regardless of skill level
- A technology strategy that uses the best technology today and maintains optionality for the future
- A data strategy that keeps your data where it is while expanding access and security
- A governance strategy that ensures regulatory compliance and business alignment
Jerod Johnson, senior technology evangelist at CData Software, explained that connecting users to the data they need—when and where they need it—is a central focus of CData’s approach to modernization. CData’s customers are currently leveraging CData to modernize in the following ways:
- Consolidating operational data into a central repository
- Moving data from on-premise to the cloud
- Deploying new data fabric, mesh, or governance strategies
- Scaling IT infrastructures with a growing business
- Connecting data between specific systems
Ultimately, a crucial aspect of modernization is addressing the sheer volume of data that many organizations are facing today. Johnson explained the CData is the preferred partner for data volume, offering reliable, affordable data replication that fuels cloud data and analytics initiatives. With support for modern, analytics-ready cloud data stores—including Snowflake, Databricks, Google BigQuery, Amazon Redshift, and more—CData offers a cloud-friendly solution with pricing based on connections, not volume, additionally offering support for both legacy and modern data sources.
For the full, in-depth webinar, featuring customer examples, detailed examinations, a Q&A discussion, and more, you can view an archived version of the webinar here.