Data Observability Ushers In A New Era Enabling Golden Age Of Data

Have we entered the Golden Age of Data? Modern enterprises are collecting, producing, and processing more data than ever before. According to a February 2020 IDG survey of data professionals, average corporate data volumes are increasing by 63% per month. 10% of respondents even reported that their data volumes double every month.

Large companies are investing heavily to transform themselves into data-driven organizations that can quickly adapt to the fast pace of a modern economy. They gather huge amounts of data from customers and generate reams of data from transactions. They continuously process data in an attempt to personalize customer experiences, optimize business processes, and drive strategic decisions.

The Real Challenge with Data

In theory, breakthrough open-source technologies, such as Spark, Kafka, and Druid are supposed to help just about any organization benefit from massive amounts of customer and operational data just like they benefit Facebook, Apple, Google, Microsoft, and Amazon. Conventional business wisdom is that more data drives faster growth of business. 

The reality, however, is quite different. Modern data pipelines are non-intuitive, inter-connected, and orders of magnitude more complex to manage than previous generations of web and enterprise applications. Corporations know that building bigger, more complex data systems alone won’t solve the problems they face every day.

The Data Observability Opportunity

When data is done right, there is no question it drives outsized business and financial performance. You don’t have to look too far for empirical evidence. One of the primary drivers for the incredible growth, profitability, and market capitalization of the big technology giants mentioned earlier - perhaps we should just call them data companies? - has been their ability to harness huge volumes of data in support of their businesses. Directly related is the fact that Microsoft, Apple, Google, Amazon, and Facebook hold the top spots in market value for US-based organizations.

What is Data Observability? 

In its simplest terms, “Data Observability” is a set of tools to track the health of enterprise data systems and identify and troubleshoot problems when things go wrong. Data Observability provides continuous, holistic, and cross-sectional visibility into complex data systems, such as the analytics and AI applications that companies would like to use to guide their businesses and personalize customer experiences. It synthesizes signals across infrastructure, application, and data layers to provide a comprehensive understanding of individual components, data pipelines, and system performance.

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