Data warehouses have transformed how companies store and manage data. By centralizing data into a single repository, overall data accessibility and quality improve a lot. A data warehouse is not a single tool but a combination of various processes and tools involved in organizing data in a structured format in a central location.  Building an ..read more

If you are a data-driven business, then you must know how crucial it is to extract meaningful insights from your data. That’s where Reverse ETL comes into play. I’m guessing you might know what ETL (Extract, Transform, Load) is. It is the process of bringing data into your warehouses. But then, what about getting this ..read more

Today most organizations are of the opinion that public APIs should be tapped into and useful information extracted there from. The same, however triggers a sound ETL solution to handle the data correctly. This blog REST API ETL Tools will talk about the various tools that will help you fetch data from Public APIs and ..read more

Have you ever opened the billing section of a BigQuery account and got a shocking surprise? You are not alone. BigQuery is a powerful tool, but this power does not come for free all the time. It can quickly deplete your budget if you do not practice good cost management. BigQuery is one of the ..read more

In the data engineering industry, managing your data is critical for driving business. Data is gathered from various sources in all shapes and forms, and without the right set of tools, it is impossible to use this data for meaning analysis.  If you work with a cloud environment, you must have heard of Microsoft Azure ..read more

Databricks is a popular and powerful unified analytics platform. It helps organizations streamline their data engineering, machine learning, and analytics tasks. As data grows and organizations understand the importance of data-driven decision-making, it becomes important to analyze and optimize the costs of data platforms being used carefully. Without careful management, organizations may end up having ..read more

The importance of data quality within an organization cannot be overemphasized as it is a critical aspect of running and maintaining an efficient data warehouse. It tells us how well a dataset meets certain criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness and fitness for purpose.  High-quality data ensures that organizations make data-driven decisions to ..read more

Batch Processing is a commonly used data integration method to capture data changes in a database. It runs on a schedule to fetch either incremental or a full data extract. However, this method is inefficient when data latency causes significant performance strain on the source systems. A more modern approach to capturing data changes was ..read more

As developers and data engineers build complex applications in Snowflake, monitoring performance is essential for ensuring smooth operation and a positive customer experience. Snowflake operations can be tracked using Snowsight, which provides tools for managing costs, tracking query history, monitoring data loading and transformations, and overseeing data governance activities.  Recently, Snowflake introduced “Snowflake Trail,” a ..read more

Organizations have begun to built data warehouses and lakes to analyze large amounts of data for insights and business reports. Often time they bring data from multiple data silos into their data lake and also have data stored in particular data stores like NoSQL databases to support different use cases. To analyze all of this ..read more