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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.

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.

Amazon Simple Storage Service (Amazon S3) is a cloud-based object storage service from Amazon Web Services that collects data from anywhere on the internet. In today's data-driven world, businesses rely heavily on seamless data integration and transformation processes to unlock the full potential of their vast data resources. But what happens if you want to move data from Amazon S3 to a data warehouse for analysis?

Built with BigQuery, Live Ramp Safe Haven enables cross-channel marketing analytics to help customers execute media campaigns.

GenAI depends on data maturity, in which an organization demonstrates mastery over both integrating data – moving and transforming it – and governing its use.

In recent years, governments across the globe have recognized the transformative potential of artificial intelligence (AI) and have embarked on initiatives to harness this technology to drive innovation and serve their citizens more effectively. These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm.

Keboola, a self-service data operations platform, has raised USD $32 million in a Series A funding round, led by the private equity business of Viking Global Investors. Keboola’s mission is to connect and integrate all company data in one end-to-end Data Stack as a Service. This new approach to the Data Stack puts customers in full control of their data with a single platform. The significant funding builds on a USD $5 million Seed round closed in 2022.