Posts by Giana Reno
10 Things a Data Quality Tool Can Do for You
Every company relies on data to make key business decisions. If that data is bad, it could lead to bad decisions—and lower profits. Do you know how to ensure high-quality data in your organization? The best way is to employ a data quality tool to identify bad data and either clean or delete it. Using…
Read MoreData Lake Vs. Data Warehouse: 3 Core Differences
Picture this: You’re a chef preparing a special meal tomorrow. You have all the ingredients you need today, but now you have to decide where (and how) to store them. Do you put everything in neat, organized containers in the fridge (like a data warehouse), or do you keep them all in one big pot…
Read MoreThe 1-2-3 Guide to Self-Service Data Ingestion
How much data does your organization ingest each day? If yours is like most companies, the amount of data you have to deal with is rapidly growing – and becoming a significant problem for your organization. According to the PBT Group, the total amount of data created worldwide is expected to grow to 180 zettabytes…
Read MoreThe Real (and Scary) Cost of Bad Data
Bad data can cost you money. It can also damage your reputation, drive good customers away, and negatively affect your entire workforce. Bad data, more often than not, results in bad decisions – and bad decisions can destroy a business. The true costs of bad data are so overwhelming that they’re scary. If you don’t…
Read MoreData Warehouse Architecture: Traditional vs. Cloud
A data warehouse is a system that gathers data from various sources and makes it available to management and others to support and improve their decision-making. Data warehouses can employ either a traditional architecture or a cloud-based one. That brings us to the traditional vs. cloud data warehouse architecture topic. Which is best for your…
Read MoreData Testing Vs. Data Observability: What Does Your Data Need?
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
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…
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