DataWarehouse

Data quality is a crucial element of any successful data warehouse solution. As the complexity of data warehouses increases, so does the need for data quality processes.

In this article, Toptal Data Quality Developer Alexander Hauskrecht outlines how you can ensure a high degree of data quality and why this process is so important.

ETL can consolidate data from various sources into an organized, reliable, and usable database. This allows businesses to employ previously unused or underused data to improve their performance.

In this article, Toptal Data Modeling Developer Alexandre Wanderer demonstrates all stages of the ETL process in building a data warehouse.

Data warehouses aren’t exactly a new concept, but industry demand for data science services, coupled with the rise of AI and machine learning, is making them more relevant than ever.

In this post, Toptal Data Warehouse Developer Chamitha Wanaguru outlines three basic principles you need to keep in mind when developing a new data warehouse.

Although database programming does not evolve at nearly the same pace as traditional application programming, recent advancements in several fields are bringing new techniques and technologies within the reach of small and independent developers.

In this guide, Toptal Freelance Software Engineer Jeffrey Shumaker explains how developers can quickly and easily tap these methods to identify database issues they may not even be aware of, and how they can build excellent data mining tools without spending a lot on expensive software licenses.