Posts by Seth Rao

Ensuring high-quality data is imperative for every organization, but did you know the role of ML and AI in data quality management? That’s right, many of today’s sophisticated data quality management tools utilize advanced machine language (ML) and artificial intelligence (AI) technology to identify poor-quality data and make it cleaner. ML and AI help to…

Data Quality Monitoring is vital for maintaining the accuracy, consistency, and reliability of your business data. As data flows through various systems, it can be prone to errors and inconsistencies that, if left unchecked, can impact decision-making, operational efficiency, and compliance. Effective data quality monitoring involves continuous assessment using various techniques and tools to identify…

Before diving deeper, let’s begin with a data observability definition to understand its role in ensuring data accuracy and reliability. What is Data Observability and Why Does It Matter? Data observability is the ability to monitor your system’s data, identify data-related issues, and rectify those issues. It’s about observing and understanding the health of your…

Organizations need to improve data quality to ensure they’re always using accurate and useful data. According to Experian’s 2021 Global Data Management Research report, businesses say that poor quality data: Improving data quality resolves these issues and results in several significant benefits, including more reliable analytics, efficient operations, and reduced costs. That is why Gartner…

Building a robust data infrastructure is essential to survive in today’s ultra-competitive environment. Do you know how to create an efficient and effective data infrastructure? There are several vital steps to take, starting with defining your data strategy and cleaning your data for the highest possible data quality. Quick Takeaways What is a Data Infrastructure?…

To successfully embrace digital transformation, businesses must fundamentally rethink their use of technology across all aspects of operations. This journey involves significant changes to hardware, software, operational practices, and company culture. At the heart of this transformation is the need for high-quality data, which is crucial for driving innovation, efficiency, and strategic decision-making. As companies…

Without adequate data error handling in a data warehouse, the data stored can become unusable. Traditional methods of data error handling rely on a rule-based approach that is difficult to manage and does not easily scale. Today, data warehouses require a more scalable solution that can autonomously monitor large volumes of data, detecting and correcting…

What data ingestion tools should you use in your organization? It depends on what type of data you’re ingesting and how fast you need it ingested. The quality of the ingested data also matters, which you can ensure by supplementing data ingestion with data quality monitoring. Quick Takeaways Understanding Data Ingestion Data ingestion is the…

In the 21st century, data has become a natural resource. Like oil or precious metals in the ground, the data created in human digital activities exist in a raw form that becomes valuable when extracted and used. The potential value of extracted, analyzed data has precipitated the development of new methods and practices for processing…