How Does Dataware Help Companies Make Better Use of Their Data?

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4 min read

Editor's Note: This is the 5th blog post in a 5-part series that describes how modern enterprises are struggling with the handling of data, making it available to applications without creating new silos, and how MapR solves these challenges by introducing a new layer of abstraction called dataware. The previous 4 blog posts can be found here, here, here, and here.

Data now lives everywhere, in many different repositories, each of which has a different way to grab the data and make it useful. The days are gone when SQL was the only language an application had to speak to access data. Now application developers must speak many languages to assemble the data needed for an application.

But must every application speak every language? No. That would make applications too complex and unmanageable. Instead, savvy companies and developers are using dataware to alleviate many of the data access challenges of today's complex enterprise environment.

Dataware abstracts the management and processing of real-time data of many different types across platforms, in the cloud, on-premises, or at the edge. They make it easier to use data across applications with the knowledge that that data is integrated and unified.

But the platform also has many downstream effects that can make a company's data more valuable overall. How?

Every users' interaction with dataware is collected and can be queried in and of itself. This generates a vast new amount of metadata about how data is being used and searched for.

Such metadata allows companies to track user behavior and identify whether anyone is accessing (or trying to access) data that they shouldn't be. This can help with governance and compliance initiatives. Companies can also optimize performance based on this information, resulting in applications that run more efficiently.

But even more valuable to businesses may be the way that companies can create a new cache of metadata that allows for previously unforeseen insights to arise. Here are two real-world examples to illustrate the benefits of dataware:

  • A design company used a data platform to help manage their overwhelming inventory of documents, which numbered close to 50 million. The platform helped to catalog and collect information on how users in the business were searching for specific documents. It recorded successful and unsuccessful searches. Based on this, it could then use the metadata to correlate new search terms to documents, even if a specific term wasn't used in a document. This meant users could more easily find what they were looking for and document search in general became more fruitful.
  • Credit card companies are constantly on guard against fraud. One pattern of behavior that indicates fraud is based on location and is called a probe transaction, in which a purchase made in one retail store is closely followed by an on-point purchase made in a far-off location. Internet transactions of low budget items that include address verification are other good examples of probe transactions. This type of behavior is a good indication that a card has been stolen. To counteract probe transactions, companies have created models to detect this behavior. Dataware can then aggregate those fraud models and present a business with data that identifies the best outcomes of each model so that fraud can be reduced.

In essence, the metadata generated by the platform makes the data more valuable and accessible. With a bit of creative thinking, this metadata can be put to use in many ways that drive value.

This blog post was published May 02, 2019.

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