Datagaps is the only company to be listed in Gartner® DataOps Tools & Data Observability market guides

One of our clients decided to change their reporting platform to Power BI and started rebuilding their reports. However, they had a large number of reports. The implementation process began with the planning of the development phase....
Data is a precious asset that has to be validated at various stages of use. One stage is at the point of ingestion, and another as it moves through your enterprise and lands in your data warehouse or data lake. Finally, when it is consumed in your data analytics platform....
What is Data Drift? Within the data space, the only constant thing is “change”. The drift in data here refers to a multitude of changes in the input data primarily in terms of frequency, aggregates, and heterogeneity. These are not regarded as errors as these types of shifts and changes...
This statistic shows a grim picture of wasted effort. But to replace CapEx with OpEx cloud data migration and cloud migration, in general, is a popular solution. Enterprises are looking for ways to scale data storage, due to AI and ML and given the volume of data being generated and...
DataFlow is a powerful application using which you can easily perform end-to-end automation of a data migration process. In DataFlow, there are different kinds of components to serve different purposes. One of them is the Code Component. It supports three kinds of languages....
Data profiling is a crucial step in the data management process, especially in the pharmaceutical industry where accurate and reliable data is essential for making informed decisions....
An Introduction to Query Builders Query Builder is a tool that allows users to create complex SQL queries without needing in-depth knowledge of the SQL programming language....
ETL stands for Extract, Transform, and Load. It is the process by which data is extracted from one or more sources, transformed into compatible formats, and then loaded into a target Database or Data Warehouse....
Type 2 Slowly Changing Dimensions are used in the Data Warehouses for tracking changes to the data by preserving historical values. This is achieved by creating a new record in the dimension whenever a value in the set of key columns is modified and maintaining start and end date for...
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