The hottest big data tools in 2025 include Amazon Aurora DSQL, Snowflake Intelligence, and the Databricks Lakebase.

That creates major challenges for businesses and organizations trying to make valuable use of their data assets. They need advanced tools to identify and inventory the data they have and where it ...

Big data is one of the most significant industry disruptors in IT today. Even in its infancy, it has shown significant ROI and has almost universal relevance to a wide cross-section of the industry.

As data flows into businesses faster than ever before time-to-insight and time-to-action are critical competitive differentiators, and the demand for fast access to information is growing. However, ...

SAN RAMON, Calif., Nov. 1 — Ventana Research today launched its newest benchmark research, an in-depth examination of Big Data Integration in businesses. The research focuses on the benefits of ...

Enterprises that wish to remain relevant in their respective markets are embracing big data, including its benefits and challenges. Data integration plays a key role in big data as it allows ...

Big data has become a heavy buzzword, promising to deliver greater customer insight at a more granular level than ever possible before. Indeed, organizations can now access a wealth of information on ...

REDWOOD CITY, Calif., March 24 — Talend, the global big data integration software leader, today unveiled Talend Integration Cloud, a powerful new solution to extend and advance the data-driven ...

Data Integration vs ETL: What Are the Differences? Your email has been sent If you're considering using a data integration platform to build your ETL process, you may be confused by the terms data ...

In life science research, data comes in many forms - structured clinical trial tables, semi-structured instrument outputs, and unstructured lab notes or images. This “variety” makes it difficult to ...

In this contributed article, editorial consultant Jelani Harper discusses how organizations can now get the diversity of data required for meaningful machine learning results. The overhead of ...