Best 5 Big Data Analytics Skills You Should Not Miss

The advent of big data in the mainstream of business world has prompted companies to rethink and rebuild their strategies and budget. Whether a business is large or just starting up; whether it is product based or service based, it cannot ignore the importance of integrating big data. It is predicted that big data, analytics sales will reach a $187 billion by 2019, which shows a staggering growth rate of 50% in the sale of big data analytics software and services. This carries clear implications that businesses are investing whole heartedly in their big data initiatives. Why should not they? Successful use of data can decide an enterprise’s fate. The question is – how to achieve success in a big data initiative? Investing a lot of money to buy the coolest software may not suffice. You need the right people in place and the right technologies in your inventory.

A recent report by Forreseter puts up a list of big data technologies in accordance with their usual or possible trajectory of maturity, success, and/or decline. This report should help us list up 5 skills that can be instrumental for the success of your business venture and which are absolutely indisputable.

5. Data Preparation

As you may already know that data preparation or data pre-processing means the manipulation of data into a form which is suitable for further analysis. This is often held as a tedious job to do; but what good data preparation software does is of great value for any analytics team. It cleanses and shapes unstructured and messy data into useful information. Data preparation consumes 60%-80% time of any data mining project and complete automation is impossible, nevertheless it is absolutely necessary.

4. Distributed data storage

This is a simple modification in data storage technology – data is stored in multiple systems. When asked for certain information, the data base presents the data as if it were locally stored. It enables the data base to be accessed over different networks. This technology really goes a long way in a global business environment. In case of a system failure the integrity of the data base is secured.

3. Data Visualization

An efficient data visualization system is essential when it comes to applying the insights drawn through data analysis in the business. This is basically the medium of communication between the analytics team and the business or production management team. A great data visualization system does not only make a digestible story out of the analytical findings but it also quickens the pace of decision making.

2. NoSQL Databases

This technology involves a large variety of data base systems. This is currently the best solution to the problem that constantly poses itself in front of analytics professionals, the problem of data storage. Today’s data world moves in a rapid pace and change is the only constancy. Developers create a great mass of structured and unstructured data on a regular basis. Traditional data storage systems are insufficient, to say the least and that is where data NoSQL databases come into play.

The various types of NoSQL databases are Graph stores, Key-value stores, Document database and Wide-column stores. This database system can secure access to large scale structured and unstructured data; enables object oriented programming. It substitutes expensive monolithic architecture with geographically distributed scale-out architecture. This technology is quite essential to the progress of any business.

1. Predictive Analytics

As the name quite clearly suggests, predictive analytics means the application of analytics to predict future outcomes on the basis of current and historical events. This involves advanced algorithms, statistical analysis, and machine learning. This technology has been around for a long time but its commercial value has been realized and focused upon in recent times. Predictive analytics has doubled the value of data driven insights. Recent developments have made it available to businesses around the world as well as increased cost-effectiveness.

Predictive analytics has taken many aspects of business and administration to a new level. It helps optimize marketing campaigns to address and attract the most potent customers as well as to retain them. It has a great role to play in fraud detection and risk reduction. It is impossible for a data centric company to thrive without integrating predictive analysis.

Technologies require tools and tools need skilled people to operate them. The success of any big data initiative depends on three basic principles –

• Identification of necessary technologies and tools in accordance with company’s goals
• Getting the right tools to get the job done
• Deploying people with the required skill set.

Keep these points in mind while strategising your big data venture and get ready to roll.