Getting Incremental Value from your Data Assets

Data Management is the key to benefiting from the current wave of emerging technologies. The Cambrian Explosion of Data tells the story of the geometric growth in the quantity of data. The amount of data has roughly grown by a factor of 16 Million over the past decade. 

Much of the growth in data is attributed to systems automation, the internet, and the internet of things. The growth in unstructured data in the past decade is greater than the growth of structured data by a factor of 15.

Organizations have struggled for decades to gain access and organize data for management reporting, business intelligence, and KPI’s. Now more than ever, organizations are demanding data driven decisions and performance metrics to compete and grow.

Historically, the challenge behind any enterprise reporting initiative has been combining the data silo’s that have been created over the past couple decades. Many mid-market and larger companies have invested in enterprise data warehouses and connecting them to reporting platforms such as Power BI, Tableau.  The usage of such patterns and platforms has proven very successful, but companies are now looking to the future, a future focused on incremental value and revolving around Artificial Intelligence (AI) and Machine Learning (ML).

47% of business executives say their companies have embedded at least one AI capability in their business processes and just 21% say their organizations have embedded AI in several parts of the business. 30% say they are piloting AI. (McKinsey)

In 2019, among companies using AI, 70% will obtain AI capabilities through the cloud. Cloud-based AI software and services will make it easier for companies to benefit from AI, accelerating their adoption and spreading their benefits. (Forbes)    

Embedding AI into a business requires an intimate understanding of the business need and the ability to access and organize the source data in order to effectively utilize the relevant Artificial Intelligence and Machine Learning platforms. 

No doubt small to mid-sized companies have some understanding of the business need and benefits of AI, however these organizations may not understand what is possible using AI or have the data management skills to obtain the type of insight into their data they are seeking. If you would like to discuss your specific situation, click here.

The pattern discussed above is reliant on Relational Database Management Systems (RDBMS) but what about all that unstructured data (Big Data) and unlocking data and patterns hidden inside these volumes of data? NoSQL fills a gap and extends the use case of classic RDBMS.

NoSQL technologies are used for the storage and quick access to unstructured data. They consist of a key value database consisting of a collection of paired identifiers (“keys”) and facts (“values”).

The combination of reporting platforms, RDBMS for structured data and NoSQL for unstructured data enables any sized organization to gain incremental insight for their data. Click here to obtain a no commitment data management assessment and discuss ideas on how to embed Artificial Intelligence and Machine Learning into your management strategy.