The reason data is getting bigger and bigger is that machines are getting involved. From smartphones and automated sensors to every mouse click and keyboard input, about 2.5 EB of data is processed every day in these easy, silent data-gathering processes.
How to process this data and draw meaningful conclusions and help from it has become very important to many companies, especially startups in the tech sector. They use this to integrate a diverse subset of the company's data to help them develop projects. That's why Entrepreneur Magazine asked AnukoolLakhina, founder and CEO of Guavus, a San Mateo-based company that develops big data analytics software, to share with its readers how to effectively utilize big data.
What's the best thing about big data?
It is, of course, "knowing what's going on right now," that is, having instantaneous data at your fingertips. If your business is able to anticipate growth from data collection, you can often quickly categorize and make informed decisions about the information you're getting, and ultimately take timely and accurate action. Or it could be said that what you see when you study data is no longer what happened in the past, but what is happening right now. This allows you to accurately understand market trends, quickly improve services, reduce costs and save time. In the process, more opportunities arise for your company to grow.
How do you get this data?
First, organize the data you already have, and then see what kind of data you want to get. This will require you to utilize almost any service-based software (such as Salesforce-type CRM systems), Excel spreadsheets, partner-related information, sales slips, and whatever else is available to you to collect the information with what's on the device.
Afterward, these data links are integrated together. This facilitates more timely and compelling decisions. The easiest way to do this work is to start with a specific question. For example, if you want to run a promotion on Tuesdays, and you set that goal, you'll need to gather all the data to plan the program. Once you've sorted out and consolidated this data - including online sales, number of promotions on social media, etc. - your business response cycle can be shortened very quickly.
A specific example?
Say an independent coffee shop owner integrates a variety of resources and offline data, including users' drinking habits, geolocation, credit card spending history, and more. This data can then help the coffee shop enhance its own personalization market and increase promotional opportunities. For example, mothers who frequent the cafe for a drink after dropping their kids off at school can take advantage of getting a free cup of kid-sized hot chocolate outside of school hours.
What are the essential tools for handling big data?
In many cases you and your staff have already more or less used big data tools, such as user credit statistics, sales records, web analytics, and CRM databases. The key is to be able to tie this data together in an easy-to-understand application that everyone can see and utilize, changing what was once a situation where only data experts could see and understand.