Virtualization Technology News and Information
New Big Data Debt Calculator Helps Enterprise Organizations Measure Emerging Data Challenges

Dremio, a stealth data analytics company, announced today a new way for enterprise organizations to quickly identify the amount of data debt that has been created by applications built to address strategic business initiatives. Dremio's Big Data Debt Calculator is a free and simple way to estimate unplanned costs that arise from the use of non-relational data management technologies such as Hadoop, MongoDB, Elasticsearch, and Amazon S3, as well as data that is spread across many sources. The calculator also gives recommendations for minimizing debt, strategies for paying it down and ensuring it remains within acceptable bounds.

Companies today are more than a decade into their digital transformation initiatives. They are digitizing key business functions with new classes of technology that are incompatible with traditional analytical workflows. Because all data has intrinsic analytical value, this tradeoff creates this analytical debt - Big Data Debt.

Many IT organizations have embraced non-relational technologies to become more agile and to deliver always on availability to a global user base; turning to alternatives for building next generation applications, third-party SaaS applications, cloud database offerings, and NoSQL. By taking this path, these organizations are trading reduced time to market for an inability to analyze the critical business data these systems create.

According to Tomer Shiran, co-founder and CEO, Dremio, "All data has a lifecycle, and for almost four decades, that lifecycle has been based on the relational model. The data, the tools for creating and analyzing the data, and the skills for mastering the data have all shared and benefited from a common approach. As the Big Data era emerged, new technologies were created to support modern data structures and to deliver to the always-connected user. These newer systems have an important role in building modern applications, however they produce data that is fundamentally incompatible with existing analytical infrastructures including data warehouses, ETL, BI and data science systems like R and Python. As a result, many organizations are collecting significant data debt."

Learn more about Dremio's Big Data Debt Calculator here.

Published Tuesday, May 16, 2017 11:01 AM by David Marshall
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