DATA ANALYTICS TRENDS TO WATCH OUT FOR IN 2019 AND BEYOND

When you open Gmail and start to answer any mail on any subject, it provides you options for answers such as “thank you”, “received document”, “I will send”, etc. immediately. How does Gmail know how to predict the kind of answers you are expecting? Similarly, if you fill up an application of opening an account or feed your information anywhere, you get messages for investments, purchase of flats, reducing your weight, and so on in your inbox quite soon.

While spam emails or text prediction might not be new concepts, this is a new trend in marketing, which happens due to your personal data transfer. Some people analyze your data and extract information about your lifestyle, needs, trends and behavior to use it for marketing. This is the latest trend in big data analytics.

Instead of relying on manual assistance to search for potential customers, predict growth and make decisions accordingly, the companies are taking the help of data science and hire data analysts to decode this information. This has become a quick, reliable and correct information provider like an ATM or a genie from a magic lamp.

In the wake of implementing sustained business models, the industry is accelerating its automation. In this technological race, tech-enabled businesses forego labored operations. Instead, they have to adapt accordingly and adopt newer ways of reaching larger audiences.

Old computers and programming languages have become obsolete. New programs and better versions of operating systems have emerged quicker than anticipation. For example, Excel is not being used as the industry standard to prepare payroll data or statistics. Instead, technologies utilize computer programs which collect and analyze data automatically. In various office departments, data entry has minimal human interaction. The data analysts use programs like python and Hadoop to analyze it and create reports to the company for its planning and decisions.

Algorithms within Google are updated frequently to collect information from the most remote corners of the internet. This forces businesses to rely on data analysis more than ever. It has penetrated blockchain, health, insurance, investments, share market, census, elections, movies, literature, beauty treatments, fashion industry, weather forecast, politics, psychology, agriculture, construction, motor industry, parent duties, migration, evolution, history, geography and many other sectors.

Sometimes, some aspects of a particular business or a subject are stored in dark data, which is not necessarily viable for analysis. Access may be restricted depending on its value. The data centers may hold this data, but leave the decision of analyzing it to the respective client.

With the demand for such new skills, the recruitment criteria have changed. Instead of MBAs and technical personnel, the need for analysts, machine learners and data engineers is on an upward trend. Eventually, as per the demand and supply policy, renowned institutions are designing courses for data analysts. In future, data analytics might as well be introduced in school curriculums as a subject.

Anyway, if you want to be a part of this data analysis revolution, you will have to be familiar with new concepts which use Artificial Intelligence such as Alexa, Viv, Cortana and Google home. Companies are in search of this talent and experts are hired immediately. Artificial intelligence will especially play a pivotal role in all data analysis. For example, it can improve the software development life cycle. Collecting big data and storing it is problematic, so similar sets of data are stored in the cloud. This turns the Internet of Things and cloud data management into new opportunities to get hired.

The most crucial aspect is digital marketing, where the customer profiles are stored as data and analyzed for purchase patterns. This process recommends products with plenty of incentives to buy without fail.

However, with every innovation comes misuse. The job of a data analyst is to analyze, but if anyone has access to your personal data, it does not remain private. Miscreants may use it to drain bank balances, blackmail, or sell it to third parties. This is and will be a challenge in implementing this innovation. As trends go, we still need to see whether data analytics will be a boon or a curse.