Guest Post
Big Data and machine learning are still relatively new terms in the world of data computing and management. Data mining is the father of machine learning that started in the 1950s with the development of applications running on databases. In 2017, both data mining and Big Data have become easy to manage with multiple computing software and data maintenance infrastructures. But this just something for the Fortune 500 or is Big Data relevant to your small business?
What Is Big Data?
Most small and medium sized businesses (SMBs) generate Big Data each day. Big Data is a term that can be used to refer to the huge quantities of data that are generated by online companies from the customer services, clients’ contacts, social media activities and website logs. You might be wondering how Big Data affects your business, and why you should be taking interest in Big Data and data mining. every aspect of our online presence is governed by both Big Data. For example, those wonderfully relevant ads you see on the right ads panel of Facebook or the sponsored ads from Google and even the shopping recommendations from Amazon are results of accurate management of Big Data gathered from your online activities.
Can Small Businesses Leverage Big Data?
The challenge that small businesses face is not the storage of mammoth quantities of data but rather the development of technologies to manage the data. New Database management systems include a matrix operator, incremental clustering algorithms and a recursive algorithm. This algorithm can generate visual elements that can be both understood and used by non-technical people. And the algorithms have made it possible for companies to analyze large graphs that include their lifelong sales activities, season’s social media activities and much more.
A Few Key Points about Big Data Management
The question we’re faced with is how can SMBs use Big Data without assigning more capital towards data management services. Here are some of the ways SMBs can leverage Big Data.
- Always remember the 3 Vs
Volume, Velocity and Variety are the 3 Vs of Big Data. These are the standard parameters that govern data base management on any platform.
- Add a C
But all three Vs become irrelevant with respect to the evolution of algorithms unless you judge the data in terms of complexity. While dealing with multiple data systems and platforms complexity becomes a mandatory parameter.
- Don’t be scared off by the volume
When it comes to Big Data and data mining, the volume is overrated. Small Businesses should not be scared away from Big Data and think it to be the exclusive domain of the big fish. Logically thinking, every big company once started out with a small quantity of data and this very factor makes the volume quite irrelevant. You can start off with what looks like a subset of true Big Data and you can slowly watch your data grow as you forge your path to success.
Big Data is not easy!
Big Data is never standing, it is never measurable and hence there is no one defined perspective to define it. Big Data is a forever changing “landscape” that commands a mélange of different algorithms capable of tackling the 3 Vs and the C with finesse and accuracy.
Big Data is not just a fad; it is a system that is here to stay. Rob Strechay, the Vice President of Zerto, the Disaster Recovery software in Boston was quoted saying, “Big Data is nothing less than a digital transformation that is changing the way most big and small companies view data collection and management”.
Most companies are already collecting every data they can get their hands on since they do not know what they might need in the near future. This is causing Big Data to grow with a boom. It has long ago left the tangible domains of storage and entered the cloud world, where they can be leveraged, extracted and used by small businesses without any hassle.
About the Author:
Sujain Thomas is a database management expert who takes special interest in data mining and Big Data services. She believes in the naturalization of Big Data and the elimination of a DBA consultant in the data mining process for technical startups and SMBs.
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