With growth in unstructured big data, RDBMS is inadequate for big data analytics. Know how to use SQL and MapReduce for big data analytics, instead.

SaaS data warehouses and low-code or no-code data ingestion tools empower the data analyst (now analytics engineer) to mostly self-serve on their infrastructural needs.

How to use SQL for Data Analysis 1:07 pm August 8, 2024 By Julian Horsey In the world of data analysis, advanced SQL techniques are essential for extracting valuable insights from complex datasets.

AI and data analytics company Databricks today announced the launch of SQL Analytics, a new service that makes it easier for data analysts to run their standard SQL queries directly on data lakes ...

PolyBase, a data virtualization feature for SQL Server, allows users to seamlessly query data from various external sources directly using T-SQL (Transact-SQL) without the need for separate client ...

Microsoft announced at the end of February 2022 that significant changes are in store across its SQL Server analytics products. To set the context, the broader enterprise IT marketplace was still ...

At the same time, streaming analytics technology is becoming increasingly accessible through open source projects, such as Apache Storm and Apache Spark, and complex event processing (CEP) engines.

May 27, 2021 — Varada, an data lake query acceleration innovator, today announced a new capability of its flagship platform designed to support text analytics workloads and help data teams deliver ...

DuckDB is a tiny but powerful analytics database engine—a single, self-contained executable, which can run standalone or as a loadable library inside a host process. There’s very little you ...

Analytics engineers have some of the most in-demand big-data roles in the industry. They're experts in SQL and a new tool called dbt, tasked with cleaning large data sets. Companies like Amazon ...