Consumer privacy has increasingly become important for businesses and individuals alike. As data is becoming more and more widespread, people are more worried about where their data is going, how it’s being used, and how it’s facilitated. This has made data security paramount and front-of-mind for many organizations.

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

The best and most desired outcome for your unique analytical application is that it delivers commercial returns, makes it is easy for your sales team to sell, and even easier for your customers to buy. To achieve these outcomes, you have to get the pricing right. There are many ways that you can price an analytics application, but the most important analytics pricing consideration is always finding the approach that makes the most sense for your unique use cases and business requirements.

With custom holiday modeling features, BigQuery users can build more powerful and accurate time-series forecasting models using BigQuery ML.

Step right up, ladies and gentlemen, and witness the grand spectacle of the digital age! In a world where data is king, where information reigns supreme, and cloud data warehouses are multiplying like rabbits, there's a technology initiative like no other— Data Warehouse Modernization! This article is the second in the series "Seven Data Integration and Quality Scenarios for Qlik and Talend," and answers everything you wanted to know about Data Warehouse Modernization but were afraid to ask.

It’s no secret that companies that listen to their customers have a greater chance at success. That is why we value our customers’ voice at insightsoftware. You use our products every day to run your organization, make critical decisions, achieve your business goals, and bring success to your own stakeholders. This approach provides you with a unique perspective on how our offerings can be enhanced with new features and tools that help you and your end users work better.

Ozone is an Apache Software Foundation project to build a distributed storage platform that caters to the demanding performance needs of analytical workloads, content distribution, and object storage use cases. The Ozone Manager is a critical component of Ozone. It is a replicated, highly-available service that is responsible for managing the metadata for all objects stored in Ozone. As Ozone scales to exabytes of data, it is important to ensure that Ozone Manager can perform at scale.

This blog series covers how to run, train, fine-tune, and deploy large language models securely inside your Snowflake Account with Snowpark Container Services This year there has been a surge of progress in the world of open source large language models (LLMs). This world of free and open source LLMs took yet another major step forward just this week with Meta’s release of Llama v2.

How to preprocess data using BigQuery ML so you can get better insights and models.

In the realm of big data analytics, Hive has been a trusted companion for summarizing, querying, and analyzing huge and disparate datasets. But let’s face it, navigating the world of any SQL engine is a daunting task, and Hive is no exception. As a Hive user, you will find yourself wanting to go beyond surface-level analysis, and deep dive into the intricacies of how a Hive query is executed.