Home Why These Three Data Management Platforms Stand Out

Why These Three Data Management Platforms Stand Out

The tremendous inherent value of data has received a lot of attention in recent years. Unfortunately, in the past, companies have often ignored the importance of the data information they gathered.

Even if they gathered customer info, they often did little it. The information sat in piles of dark data that remained unanalyzed and unattended on forgotten hard drives or cloud-based storage sites. At other times businesses did make an effort but used incorrect data in the process. In fact, in 2016, a report claimed that bad data was costing the U.S. a staggering $3.1 trillion per year.

Struggles like these have led to a rise in the number of data management platforms (DMPs) available. Each tool offers to perform a similar set of items: to identify, collect, organize, and analyze data throughout an organization’s activities. Analysts can then distill this varying 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 edge. With that in mind, here are three of the best DMPs available, as well as the unique selling points (USPs) that help each one 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 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 fix any potential issues before they arise. This helps to keep things running like a well-oiled machine. At a glance, the platform is able to offer a comprehensive, cross-section view of a business’s data regardless of the form, source, technology, or scale of the incoming information.

The need for data reliability is important, and it is a benefit trumpeted by other tools as well. For instance, fellow DMP Monte Carlo heavily focuses on the reliability aspect of its data management tool. But Acceldata goes further by ensuring that its data isn’t just reliable but also understandable.

In other words, humans can use the program in an understandable manner to reduce risk and increase the speed of execution. This enables a company’s data strategy to keep in lock-step with the organization’s larger activities and goals.

2. Unravel

For up-and-coming DMP platform Unravel, simplicity is key. The data management company’s tool works like most DMP software. It can track, analyze, and maintain data across an organization’s various APIs and touchpoints.

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

Unravel emphasizes factors like comprehensive analysis and full-stack visibility. The company also provides specific insights that pertain to each of its customer’s circumstances. It also provides AI-powered recommendations for how to address each issue.

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

3. Pepperdata

Pepperdata is another data management platform that takes observability seriously. The brand strives to create enhanced visibility and offer operational insights and recommendations for solutions.

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

Given time, this doesn’t just help you identify and resolve issues. It can also help you understand how your system works on the back end.

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

There are countless data management platforms already in existence, with more being created every day. However, simply using a DMP isn’t a dependable solution. Instead, it’s important to look for the specific traits that help each platform stand out.

Data observability creates a more seamless, dependable, and comprehensible experience. Additional factors like reliability, simplicity, and added insights can make or break your DMP adventures, as well.

So consider what kind of tool you’re looking for. What will benefit your business the best? Once you’ve isolated that X factor, you can look for that capability in the DMP platform that you choose.

This ensures that you won’t just be collecting and analyzing data the right way. You’ll be able to creatively use it to your advantage, as well.

Image Credit: nataliya vaikevich; pexels; thank you!

About ReadWrite’s Editorial Process

The ReadWrite Editorial policy involves closely monitoring the tech industry for major developments, new product launches, AI breakthroughs, video game releases and other newsworthy events. Editors assign relevant stories to staff writers or freelance contributors with expertise in each particular topic area. Before publication, articles go through a rigorous round of editing for accuracy, clarity, and to ensure adherence to ReadWrite's style guidelines.

Deanna was an editor at ReadWrite until early 2024. Previously she worked as the Editor in Chief for Startup Grind, Editor in Chief for Calendar, editor at Entrepreneur media, and has over 20+ years of experience in content management and content development.

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