6 Essential Things To Look For In Your Data Analytics Platform

December 11, 2017
Digital Analytics Platform

6 Essential Things To Look For In Your Data Analytics Platform

As more and more organizations are turning to Big Data and advanced analytics to unlock the true value of their data, the competition between data analytics vendors is heating up.

Most organizations have evolved passed the initial hype around Big Data where they wanted to work with it just because everyone was doing it. Now the expectation is that an investment in data and analytics will translate into a measurable ROI, from helping to manage the day-to-day operations to shaping long-term strategy. In the finance industry in particular, data discovery tools are creating opportunities to detect and fight fraud in ways that were not possible before.

Admittedly, as one of the players in this industry, our opinion of what makes or breaks a platform is biased. Nevertheless, this list of 6 essential criteria should narrow down your search for the right vendor.

Note that these are essentials for top performing data analytics tools. All vendors will promise to “do more with your data” but we are not all created equal: the ones that don’t live up to these criteria shouldn’t make the cut for your business.

6 Criteria for an Outstanding Data Analytics Platform

  1. 1

    Ease of Onboarding and Use

    A minimum learning curve and little to no change in existing hardware or workflows will get you up and running as soon as possible. But that’s just the start. If you want the tool to become a core part of your long-term data strategy, employees not only need to be able to use it intuitively, but must actually love using it because it makes their job easier.

  2. 2

    Works with Disparate Data Sources

    There are numerous opportunities for data analytics when a platform can truly integrate and correlate various types of data in one place. There are ATMs, POS systems, cameras, sensors, social media chatter, web analytics, discount programs, loyalty programs, etc. All of these systems create data in many different forms: structured, unstructured, or a mix of both. The goal is not to analyze them individually, but for them to be combined to create unique contextual insights. As Mark Smith, CEO of Ventana Research, wrote: “Big Data is broken without integration”.

  3. 3

    Facilitates Collaboration

    Data discovery can benefit an entire organization or an individual department, but decisions are hard to come by without some form of discussion or collaboration. While it’s easy to believe that an organization has a hard time sharing knowledge across departments, what is more disheartening is the concerning lack of information sharing within individual departments. A centralized platform for detecting suspicious activity and managing fraud investigations gives employees and investigators a location where alerts, reports and important information can be shared, enabling them to work together to expedite investigations. With the Ever-Changing Threat Landscape, Knowledge is Power.

  4. 4

    Scalability and Evolvability

    A good solution works for your needs today but might become obsolete just a few years from now. A great solution will be flexible enough to grow and evolve as your business needs change and your data strategy grows. This is important as it will help keep you up-to-date with the rapidly changing needs of investigators who deal with fraud and will allow you to better manage the increasing volume and variety of data your organizations interacts with on a daily basis.

  5. 5

    Visualizations and Dashboarding

    The purpose of using a new data discovery platform is not just to see your data in one place, but rather to see your data in ways that help drive and improve decision making. A great data dashboards will allow you to absorb and understand what’s happening in your business in a short amount of time. Whether you have ten minutes to spend looking at your data or ten hours, powerful visualizations will enable you to pinpoint outliers and action items to help you effectively perform your duties. And remember, these visualizations serve as a top layer to larger datasets. By pinpointing where your time is best spent, you’ll decrease the time spent drilling-down into these large data sets while improving the quality of evidence you are able to collect.

  6. 6

    Keeps Your Data Free and Open

    In a recent blog post, Vishal Kumar, CEO of Cognizeus, explained the importance of this: “A good product design should not keep customers sticky by keeping their data hostage. A good tool should bank on its features, usability and data-driven design.” He believes that data and it’s knowledge should be easy to import/export to common formats (csv, xml, PDF, etc.). This allows you to leverage 3rd party tools more seamlessly so you can get the most benefit out of all of your data discovery investments. Keeping your data free will play an instrumental role in fulfilling the criteria mentioned above, i.e., visualization, collaboration, and ease of use.

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