Siva Prasanna
Data analytics is analyzing raw data for drawing conclusions in the present scenario. It has been used in various sectors like business, scientific researchers, weather predictions etc., It is a valuable tool in the business but the way of its use is rapidly changing. With the advancement of Artificial Intelligence and Machine learning more and more data is generating every day which is needed to be interpreted. This is the reason for the increase in the demand for a data scientist in recent years. It will surely be a promising career in the next 4 years.
Data analytics will be the major tools used while making any business decisions at present. By 2020 it was estimated that almost 90% of the company’s strategy will explicitly mention information as an important and analytic company asset as an important competency. Data analytics is majorly used for designing business strategies and to take both long-term and short-term decisions in the business.
With the help of Data analytics, we can estimate the inefficiency of the business and can reduce the expenses wherever necessary which in turn results in the extra income.This is a fast-moving field which may vary in the next moment. Here are some of the points we must pay attention to grasp the current state of big data analytics. Achieving good results with big data starts with adequate system capacity. When leaders engineer the right solution for a large data environment, hardware can easily process its workload, and people don’t have to run around trying to solve network capacity problems.
1.Unstructured Data Multiplication:
In the past data is used to be in a certain format and is structured. But in recent years, the data will be collected in the form of audio and video which is more like unstructured form. Because we get more unstructured data, we capture more types of video and audio and non-numerics and above that, we develop a stronger type of technique for analyzing that data and keeping it in a structured format. The organisation can turn the unstructured data into a structured format which is making into useful information.
2.Need For Real-Time Models:
In the past data analytics are used to achieve long term goals. It means in order to take any business decision, the data of 1 year will be analyzed. But the scenario had changed right now which is a real-time data analytics. It was estimated that by 2022, 30% of customer interactions will be affected by real-time location analysis.
A real-time model will be more like a person who is vegan and walks into Georgia Aquarium just to know what kind of research is going on there. We know that she is a vegan. This goes into personalization too, but the point is that the algorithm that is applied in real time is what will change the action or how the aquarium can adjust at that time.
3.Deliberate data-culture initiative:
Businesses now-a-day are data inspired and integration of data into their company culture. Data culture is a type of absorption, readiness if you will be accepted and in the sense of believing in results or solutions that come from analysis. Data science professionals and Analytic groups are creating solutions and preparing them to answer all the business questions.
The data culture may be hard for traditional professionals to grasp. There will be more initiatives which are deliberately intended for the absorption of analytic solutions.
4.Citizen analyst/Tool reliance:
Analytic tools will be understood by the citizen analysts with more of packed analytics. With the help of these people can understand the basics of analytics. Without deep statistical expertise, it will become more digestible. This is mainly because businesses don’t have the time to teach about these analytics. People who know about the deep understanding of this analytics are tool creators and buyers. Then those who know the business and know how to use the tool are those who apply the tools and answer the real business questions
5.Mass Personalization:
When it comes to customer experience, personalization is everything and analytics plays a major role. Personalization becomes very intimate, helping products and services get closer to their customers. The coupons generated are not just random, they are personalized for a specific purchase. Algorithms even know the personal information like the colour of the hair you have, how many kids you have.
6.Automation and AI:
It is estimated that by 2023 there will be more computational resources used in AI will be increased 5X when compared to 2018. And AI will be in the top category of infrastructure decisions.AI and automation will be more progressing and becoming more complex and dynamic. For creating new and fresh models there are ways to the automation process to get updated automatically without processing any manuals.
