Given that data is the lifeblood of modern enterprises, the specter of data breaches looms large. The 2024 Snowflake data breach sent shockwaves through the tech industry, serving as a stark reminder of the ever-present threats in data management. While the cause of the breach came down to a combination of an aggressive hacking campaign […]
How AI Is Changing SQL for the Better
Structured query language (SQL) is one of the most popular programming languages, with nearly 52% of programmers using it in their work. SQL has outlasted many other programming languages due to its stability and reliability. SQL doesn’t change dramatically from version to version, and that consistency, combined with a logical design that allows it to deliver […]
Generative AI Is Accelerating Data Pipeline Management
Data pipelines are like insurance. You only know they exist when something goes wrong. ETL processes are constantly toiling away behind the scenes, doing heavy lifting to connect the sources of data from the real world with the warehouses and lakes that make the data useful. Products like DBT and AirTran demonstrate the repeatability and […]
ETL Automation Best Practices
In data management, ETL processes help transform raw data into meaningful insights. As organizations scale, manual ETL processes become inefficient and error-prone, making ETL automation not just a convenience but a necessity. Here, we explore best practices for ETL automation to ensure efficiency, accuracy, and scalability. We also mention some of the best ETL tools […]
10 Advantages of Real-Time Data Streaming in Commerce
While early science fiction shows like “Buck Rogers” (1939) and “The Fly” (1950) depicted teleportation technology, it was Star Trek’s transporter room that made real-time living matter transfer a classical sci-fi trope. While we haven’t built technology that enables real-time matter transfer yet, modern science is pursuing concepts like superposition and quantum teleportation to facilitate information transfer across any distance […]
How to Become a Data Engineer
The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. A data engineer needs to have a solid understanding of commonly used scripting languages and is expected to support the steady evolution of improved Data Quality, […]
Fundamentals of Data Virtualization
Organizations are increasingly employing innovative technology called “data virtualization” (DV) to tackle high volumes of data from varied sources. Data virtualization is widely used in enterprise resource planning (ERP), customer relationship management (CRM), and sales force automation (SFA) systems to collect and aggregate multi-source data. From multi-sourced data acquisition to advanced analytics, this technology seems […]
Data Activation: The Key to Taking Data Reports to the Next Level
Let’s talk about an inconvenient truth: For the typical business, data reporting has a tendency to fall short of producing the desired outcomes. Despite the significant resources that organizations often invest in producing data reports – and in the data collection, governance, and analytics processes that happen prior to reporting – the people who actually […]
The Fundamentals of Data Integration
Data integration uses both technical and business processes to merge data from different sources, helping people access useful and valuable information efficiently. A well-thought-out data integration solution can deliver trusted data from a variety of sources. Data integration is gaining more traction within the business world due to the exploding volume of data and the […]
Best Practices in Data Pipeline Test Automation
Data integration processes benefit from automated testing just like any other software. Yet finding a data pipeline project with a suitable set of automated tests is rare. Even when a project has many tests, they are often unstructured, do not communicate their purpose, and are hard to run. A characteristic of data pipeline development is the frequent […]