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Why These Three Data Management Platforms Stand Out

The enormous intrinsic value of data has received a lot of attention in recent years. Unfortunately, in the past, companies have often overlooked the importance of the data they collect.

Even though they collected information about customers, they often did little. The information was in piles of obscure data that went unscanned and unattended on forgotten hard drives or cloud storage sites. At other times, companies have made an effort but used incorrect data in the process. In fact, in 2016, a report claimed that bad data was costing the United States a staggering $ 3.1 trillion a year.

Such struggles have led to an increase in the number of data management platforms (DMPs) available. Each tool offers to perform a similar set of elements: to identify, collect, organize and analyze data throughout the activities of an organization. Analysts can then distill this variable information into meaningful statistics and actionable recommendations.

Why these three data management platforms stand out

With so many data management platforms available, it can be difficult to decipher which ones have an advantage. With that in mind, here are three of the best DMPs available, along with the Unique Selling Points (USPs) that help each stand out from the crowd.

1. Acceldata

Acceldata is a growing DMP that focuses on data observability. The platform uses AI / ML to manage all the data layers involved: the infrastructure layer, the data layer, and the data pipeline layer. According to its website, data pipelines are like modern supply chains for digital information.

For Acceldata, the primary goal is to keep a company’s data supply chain optimized and reliable. Its data observability platform identifies potential errors in order to resolve potential issues before they arise. It helps keep things running like a well-oiled machine. At a glance, the platform is able to offer a complete cross-sectional view of a company’s data, regardless of the form, source, technology or scale of incoming information.

The need for data reliability is important, and it is also a benefit touted by other tools. For example, his colleague DMP Monte Carlo focuses heavily on the reliability aspect of his data management tool. But Acceldata goes further by ensuring that its data is not only reliable but also understandable.

In other words, humans can use the program in an understandable way to reduce risk and increase speed of execution. This keeps a company’s data strategy aligned with the organization’s broader business and goals.

2. Untangle

For the emerging DMP platform Unravel, simplicity is key. The company’s data management tool works like most DMP software. It can track, analyze and manage data across different APIs and touchpoints in an organization.

However, Unravel takes it a step further by making them as simple as possible. The software takes the extremely complex elements of a modern technology stack and reduces them to an optimized and easy to understand level.

Unravel emphasizes factors such as full analysis and full stack visibility. The company also provides specific information that relates to the situation of each of its customers. It also provides AI-based recommendations on how to fix each issue.

Essentially, Unravel’s goal is to take customers by the hand and guide them through the process of data observability from start to finish. While part of this process is left in the hands of the AI, it doesn’t change the fact that simple, easy-to-understand results are essential.

3. Pepperdata

Pepperdata is another data management platform that takes observability seriously. The brand strives to create increased visibility and offer operational information and solution recommendations.

Along with these common data observability activities, Pepperdata uses machine learning automation. ML aspects of software follow the sequential aspects of a problem, tracing it step by step through your system.

Over time, it doesn’t just help you identify and fix problems. It can also help you understand how your system is operating in the background.

Not every user might need this information, but the ability to deepen their knowledge and understanding can be a huge selling point for many customers. This is especially true for those who feel overwhelmed by the ephemeral nature of a modern technological work environment.

There are already countless data management platforms, and new ones are being created every day. However, simply using a DMP is not a reliable solution. Instead, it’s important to research the specific features that help each platform stand out.

Data observability creates a more transparent, reliable and understandable experience. Additional factors such as reliability, simplicity, and additional information can also make or break your DMP adventures.

So think about what kind of tool you are looking for. What will best benefit your business? Once you isolate this X factor, you can research this ability in whatever DMP platform you choose.

This ensures that you won’t just collect and analyze data the right way. You can also use it creatively to your advantage.

Image Credit: nataliya vaikevich; pexels; Thank you!

Deanna ritchie

Editor-in-chief at ReadWrite

Deanna is the editor of ReadWrite. Previously, she worked as an editor for Startup Grind and has over 20 years of experience in content management and content development.

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