Analytics

As analytics technology evolves, so do user needs and expectations. Many customers approach us hoping to boost their application’s analytics capabilities, which are often struggling to meet user demand.

Data analytics tools help your organization understand the insights in your data through custom dashboards, reports, applications, and other visualizations. This software category covers a broad range of capabilities and use cases, from drag-and-drop, no-code dashboard creation software to end-to-end data extraction, analytics, and management platforms. We picked eight of the top data analytics tools for 2024 by referencing G2 ratings and reviews.

Apache Iceberg’s ecosystem of diverse adopters, contributors and commercial support continues to grow, establishing itself as the industry standard table format for an open data lakehouse architecture. Snowflake’s support for Iceberg Tables is now in public preview, helping customers build and integrate Snowflake into their lake architecture. In this blog post, we’ll dive deeper into the considerations for selecting an Iceberg Table catalog and how catalog conversion works.

Deliver faster marketing insights with governed data movement and democratization.

Data security will remain one of the biggest concerns for businesses this year. According to IBM, the average data breach in 2023 cost 4.45 million - and 82% of that involved data stored in the cloud. Damages from cybercrime, including the cost of data recovery, could total $10.5 trillion annually by 2025, causing more business owners to review their data security protocols. Which specific changes should you implement in the next 12 months?

Integrate YugabyteDB with BigQuery using CDC and why you would want to.

Data integration is essential for any competitive business. The ability to sync all your data from disparate sources powers better insights, analysis, and ultimately faster business decision-making. Change data capture (CDC) is one element of data integration that focuses on keeping data accurate with near real-time updates as soon as data within a data source changes.

Microsoft SQL is a popular relational database management system organizations use to manage and store data. As data volumes grow, extracting, transforming, and loading data has become essential for many businesses.

Like peanut butter and jelly, ETL and data modeling are a winning combo. Data modeling can't exist without ETL, and ETL can't exist with data modeling. Not if you want to model data properly. Combining the two defines the rules for data transformations and preps data for big data analytics. In the age of big data, businesses can learn more than ever about their customers, identify new product opportunities, and so on.