Big data has been dominating the IT mindshare for the last few years. And, with a slew of new technologies, i.e. in-memory database, NoSQL, machine learning, and cloud added to the Big data - Hadoop ecosystem, IT is left to grapple with reality vs. hype. Where do you begin, and how do you proceed? McKinsey, in a January 2015 article - "Getting Big Impact from Big Data" - makes these recommendations:
"Visualization tools… are putting business users in control of the analytics tools by making it easy to slice and dice data, define the data exploration needed to address the business issues, and support decision making," writes David Court. Earlier in the article he says "…analytics specialists builds models targeted to specific use cases. These models have a clear business focus and can be implemented swiftly."
Sensor data, i.e. time-series data from aircraft or ground assets or from manufacturing operations, has its own flavor of bigness - along with its three V's - volume, velocity, and variety to make up the industrial big data. But we have successfully dealt with it across numerous industries - in power generation, oil & gas, chemicals, pharmaceuticals, metals and mining, paper & pulp, utilities such as water, gas and electric transmission and distribution, critical facilities, data centers, and others.
And, in working with our customers, we find self-service data analytics using models targeted to specific use cases is key to rapid insights - whether it is small data or large data, or even big data. Attend this session - we will explore the various ways to getting insights from data.