Big Data Quality: Mastering Data Quality in the Age of Big Data

From the second data enters your enterprise and begins to move, it is vulnerable. Data in motion flows through many systems before it may be analyzed to derive valuable information for better business decisions.  Data in motion is at the most vulnerable stage—not only because of the nature of the information itself, but because of […]

Worried about Cloud Vendor Lock-In? Follow These Best Practices

Hybrid and multi-cloud strategies can enable greater cost control and scalability for fast-growing big data. That is likely why 84 percent of enterprises have a multi-cloud strategy in 2020.  Though that is the case, many organizations still maintain and integrate the enterprise mainframe on the multi-year road to the cloud. Seventy-one percent of Fortune 500 companies are […]

Best Practices in Data Storage: What Types of Data Should be Retained?

Even if you analyze your data in real time, storing data for extended periods is important for compliance and other reasons. But what types of data should be retained and how long should you keep it? Keep reading for some insights on data storage. Data analytics requires data storage These days, real-time data analytics should […]

5 of the Hottest IT Trends (and How Mainframes Play a Role)

Mainframes were developed long before anyone was thinking about the trends and technologies that define modern computing. Concepts like open source software were decades away from emerging when the first mainframes were deployed in the 1950s. Other modern IT trends and technologies, such as Docker, continuous delivery, and DevOps, did not emerge until more than […]

How to Clean Big Data for Trusted Insights

You’ve probably witnessed it, and maybe are doing it. Many organizations are just dumping as much data into a data lake as they can, trying to get to every data source in an enterprise and putting all the data into the data lake. We see it here at Precisely, with the vast amount of data […]

Data Quality in Healthcare: 3 Real-Life Stories

Data quality is crucial, though there are few industries in which it’s a life-or-death issue. The healthcare field is a notable one – a missing value, an additional value, or the wrong value could all lead to serious injury or even a fatality.  Healthcare organizations must take steps to improve data quality to better protect […]

How to Improve Big Data Quality for Bigger Enterprise Insights

We’re dealing with more data in the enterprise than ever before. Headlines blare that “data is valuable” but, that’s only true if the information you have is of high quality. The question becomes, how do you know if your data is high quality?    This post explores the concept of big data quality and why […]

4 Ways to Use Dark Data

If you’re like most organizations, you collect a lot of dark data – which means data that you don’t put to work. But your data doesn’t have to stay dark. Keep reading for examples of ways you can put it to use to gain new insights. The sources of dark data Before discussing use cases […]

Highly Available Data: Why High Availability Is Not Just for Apps

High availability is a buzzword in IT today. Usually, it refers to applications and services that are resistant to disruption. But it should also apply to your data. Here’s why. What is it? High availability refers to the ability of an application, service or other IT resources to remain constantly accessible, even in the face […]

Why Data Quality Makes or Breaks Your Big Data Operations

What drives big data success? Your first thought might be analytics accuracy or the amount of data you have available to process. But if you’re not thinking about data quality, you may be undercutting the effectiveness of your entire big data operation. What is data quality? Data quality refers to the ability of a given […]

Don’t Let Lack of Big Data Quality Drive Bad Business Decisions

In the past decade, big data has made headlines for its ability to provide answers to crucial questions. However, what these stories tend not to focus on is that big data is only useful when you have high levels of data quality. If you don’t, you won’t be able to make good decisions.  The issue […]

Firefighting, Running and Beyond: Big Data Success Stories

You hear about big data all day long, but do you know how it is used in the real world? Here’s a look at examples where big data solved real problems. Big data examples in practice One of the reasons big data has become so popular is that there are so many things you can […]