Where change is welcome.
Exploding data growth has led to a search for a robust, scalable, high performance data solution that can accommodate growing data demand. There are many solutions available, but the data warehouse and data lake are two of the most popular. …
The primary goal of machine learning (ML) is to perform a task more efficiently using models, which only becomes possible if the ML models are available for end users. Most view ML deployment as an art, requiring careful collaboration between…
The data lakehouse is a relatively recent evolution of data lakes and data warehouses. Amazon was one of the first to use a lakehouse as service. In 2019, they developed Amazon Redshift Spectrum. This service lets users of its Amazon…
Post Updated June 14, 2023 Python and SQL are the two most common programming languages crucial in the day-to-day work of data engineers and scientists. So for anyone looking to delve into data, choosing one of these languages to learn…
This post was updated on February 24, 2023 The best way to understand something is through concrete examples. I’ve put together seven examples of data pipelines that represent very typical patterns that we see our customers engage in. These are…
Spark is a widely used platform for businesses today because of its support for a broad range of use cases. Developed in 2009 at U.C. Berkeley, Apache Spark has become a leading big data distributed processing framework for its fast,…
One crucial part of Big Data is streaming data. As the name suggests, streaming data refers to data that undergoes continuous generation from multiple sources like social media, CRM, and ERM platforms. Handling and analyzing streaming data can be complex,…
A successful data migration strategy involves moving data from one source to another with as little friction as possible. That friction usually comes in cost, data loss, or downtime accessing the target or destination data sources. A good migration design…
This blog post was updated March 14, 2023 Data pipeline architecture refers to the design of systems and schema that help collect, transform, and make data available for business needs. This data pipeline architecture involves tools and technologies for data…
The benefits of data warehouses are numerous and they have become essential for organizations dealing with massive amounts of data, and while other alternatives come to market their adoption remains on the rise. This increased adoption accounts for a projected…