10 Common Misconceptions About Big Data

10 Common Misconceptions About Big Data

1. Big data is a new concept –Actually, big data has been around more than 20 years. The only things that have changed are how large the volume is, and thus, how we capture, store, analyze, and use it.
2. Big data is complicated – Today’s systems are designed to eliminate complexity. They are automated, flexible and crafted to meet your specific business needs—without human intervention and errors.
3. Big Data is expensive – Big data solutions now exist that help you identify problems and react to them instantaneously, saving time and money. Services exist that allow you to only pay for the storage and computing capacity you actually use and yet give you the option to scale virtually infinitely. The reality is that your business can’t afford to not have these systems in place; data is your most valuable asset.
4. Big data requires having petabytes of data – How much data you have matters, but not as much as the type. Using KPIs and tracking metrics, you can know what data to collect and understand how it can be used in making smart, data-driven business decisions that generate ROI.
5. Big data is reserved for data scientists – Dashboards make big data analytics accessible to anyone, from average employees to end-users to data scientists, so they can get data-driven insights and make data-driven decisions at the click of a button. Most companies already employee people capable of helping them gather the insights they need using tools and apps, minimizing the need to add an experienced data scientist to the payroll.
6. Big data is just technology – Big data set storage and analysis rarely require a major change in your IT department since we have all kinds of analysis options from the cloud to the software.
7. Big data is magic – Unfortunately, it doesn’t come with a magic easy button to push that delivers a competitive advantage or insights. You need people with the skills and experience to know how to make use of it and organizational cultural support to put it into action.
8. Big data doesn’t apply to me – Even the smallest companies produce a staggering amount of data that can offer real results. Think about your own customer data, sales data, website data, resource data, process data, and so forth. Bringing it all together can deliver insights into ways to better optimize your pricing, marketing, products, etc, no matter what your size is.
9. Big data provides precise answers – Big data is as only as good and the data inputs and analysis methods used to interpret it.  It provides patterned or generalized insights that require human interpretation, rather than precise answers.
10. Big data is about Hadoop – While Hadoop is typically at the foundation level of big data options, it is only one of the tools and platforms big data professionals find useful.

Do you know of any additional Big Data misconceptions not listed here? Let us know in the comments and we’ll help steer you through the maze of misinformation to Big Data success.