Posts by Seth Rao
Data Testing or Data Observability: The Ultimate Guide to Data Quality Enhancement
Poor-quality data is a blight on every organization that depends on data to run its operations. Using inaccurate and incomplete data can affect operations and long-term strategic planning, lead to bad decisions, and make a company less competitive in the market. You can address the problem of poor-quality data through data testing and observability. You…
Read More10 Common Data Quality Issues (And How to Solve Them)
Data quality is essential for any data-driven organization. Poor data quality results in unreliable analysis. High data quality enables actionable insights for both short-term operations and long-term planning. Identifying and correcting data quality issues can mean the difference between a successful business and a failing one. What data quality issues is your organization likely to…
Read MoreHow to Build a Unified, Scalable Cloud Data Lake – Key 4 Step Process.
Large, flexible, and powerful. No, not the Stay Puft Marshmallow Man. Cloud data lakes can store large amounts of data, are flexible enough to store a wide range of structured and unstructured information, and are a powerful tool for business analytics across diverse industries. This guide is the only one you’ll need to understand what…
Read MoreHow to Build the Perfect Analytics Stack?
How effective is your organization’s analytics stack? You need the right stack of technologies to maximize data ingestion, transformation, storage, and analysis. A less-effective analytics stack can result in poor data quality and often unusable data. When you build the perfect analytics stack, you’ll be able to more effectively manage your day-to-day operations and make…
Read MoreWhy Every Catalog Needs a Data Trust Score?
Does your data catalog need a data trust score? With the increasing use of data catalogs in data management, the answer is a resounding yes. Assigning a data trust score to a catalog ensures that the data within is trustworthy for use in both day-to-day and long-term decision-making. Quick Takeaways What Is a Data Trust…
Read MoreData Quality vs. Data Trustability: Understanding Key Differences and Why They Matter
Do you know the difference between data quality and data trustability? Both are concerned with data quality and usability but differ in how they approach the issue. Data quality tracks the accuracy of data within a data pipeline. Data trustability has a larger scope, using machine learning to identify data errors from data creation to…
Read MoreUnderstanding Data Trust: How to Enhance Data Quality and Trustworthiness With Trusted Data Formats?
Do you trust the data used by your organization? A data trust score measures how much you trust your data and is based on how accurate, up-to-date, and relevant your data is. In the end, the data trust score reflects your data’s quality—high-quality data is more trustworthy than low-quality data. Quick Takeaways What is Data…
Read More5 Critical Things You Should Know About Data Trustability
How much do you know about data trustability? Do you know how data trustability relates to data quality and data observability? Do you know how it works within a data pipeline? Do you know why your firm needs it? Data trustability is the next step in data quality. It goes beyond both data monitoring and…
Read MoreData Pipeline Observability: What It is and Why It Matters
Data observability is the big buzzword these days, but do you know what it is or what it does? In particular, do you know why data observability is important for data pipelines? You use a data pipeline to move data into and through your organization. You use data observability to ensure that your data pipeline…
Read MoreWhat is Data Observability for Data Lakes and How It Transforms Management?
Do you know what data observability is or how to use it with data lakes? Large organizations are increasingly using data lakes to store large volumes of data from various sources, and data observability can make that data more usable. It’s all a matter of creating a more reliable and efficient data pipeline—at which data…
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