In the world of big data, are you an analytical producer or an analytical consumer?
Don’t worry; one isn’t necessarily better than the other. In fact, analytical producers and consumers need each other, as we explain in our white paper, “Big Data Analytics in Action.” Analytical producers use data mining, predictive analytics, machine learning and natural language processing to produce models, which analytical consumers use to drive the business forward.
Big data is the plumbing; analytics is the business context.
Another important topic we cover in the paper is the difference between big data and analytics, a difference that sometimes gets blurred in the conversations between IT and business managers.
Big data is about the storage, speed, performance and functionality of hardware and software pulling information into your organization. Analytics is about enabling informed decisions and measuring impact on your business. Big data drives innovation in analytical technologies, and this white paper introduces you to the most prevalent of those analytical technologies, as shown in the diagram:
- Data Preparation – As data moves faster and in higher volume from more disparate sources, both producers and consumers need it aggregated.
- Data Exploration – With web-based tools, users can visualize and drill deep into data.
- Search – Users can also gain insight from unstructured data with tools that allow them to mine it.
- Advanced Analytics – Techniques like machine learning, forecasting and optimization reveal patterns in the data.
- Deployment and monitoring – The key to making repeatable decisions in the organization is to combine predictive analytics and business rules.
Read the white paper
The white paper also contains concrete applications of analytics and big data in marketing, finance, healthcare, pharmaceuticals and manufacturing, along with a series of tips to ensure success in your next analytics project.