DATA ANALYTICS
DEFINITION
Data analytics is the study through which we can examine the raw data so that purposeful conclusions can be drawn from it. Data analytics can be -used in many industries and organizations. Its main aim is to make decisions and to approve or disapprove the current model or theory.
It must be kept in view that data analytics is entirely different from data mining regarding purpose and method of analysis. Data analytics can be further divided into two parts:
The first one is exploratory data analysis (EDA) in which new aspects of data are discovered, and confirmatory data analysis (CDA) were already present hypothesis is either accepted or rejected.
Moreover, Qualitative data analysis (QDA) is mainly used in social sciences where conclusions are made by non-numerical data. In short, the information does not consist of facts and figures. In business, data analysis is used to see the working of a system, whether it is handling the data correctly or not. (Rouse, 2008)
HISTORY OF DATA ANALYTICS:
The history of data analytics dates back to mid-1950. The evolution started with the starting of analytics 1.0. It all started with the emergence of descriptive analytics and reporting activities. Small teams in organizations used to carry out this work. Their main aim was to work on the internal decision support.
Still today, Analytics 1.0 is functioning in many places. After that, a company called SAS came up with some new packages, offers, and latest methods. Only 7% of the population used this new technique while others still used old methods.
Analytics 2.0 was introduced a couple of years ago in the Silicon Valley. This discovery gave rise to applications related to unstructured information. Mostly the data and information in big industries are unstructured. (ROBERT HANDFIELD, 2013)
ADVANTAGES OF DATA ANALYTICS
Most importantly, it allows the company to see the faults and errors which can affect their working. This helps the company to control the rate of loss. Secondly, it is a great way from the competitive point of view. It gives more opportunities for the company to develop high methods and strategies in a very short duration of time. It also provides an insight into the business and the customers. The data collected through this matter can help the company to improve and strive for success. In can also be used in health care facilities to manage their data. This method ensures better health care for the people.
DISADVANTAGES OF DATA ANALYTICS
Data analytics can also impose drastic changes in the industry. First issues arise in the logistics field. The company has to mold their entire setting because the flow of data becomes static instead of periodic.
Secondly, this method requires expertise and sophistication, and if the industry fails to operate it correctly, the data of the company may get affected. Thirdly, many people like everyday citizens and politicians face the privacy issue. (ciklum, 2015)
CHALLENGES OF DATA ANALYTICS
Data analysis may face accurate and precise financial risk management and assessment. Real world has many complexities which the data analytics may fail to cater. Business intelligence and power of prediction can help to provide these problems. Secondly, it becomes difficult to unite business and analytical data into the real-time. Major reason behind is that the flow of data is static instead of periodic. The speed of analytics is increasing day by day and business has to maintain its standards by managing the data in an excellent manner without any flaws and errors.
Thirdly, social ROI should be measured correctly by using a financial metric. In the cases of reduced costs or increased deal flow, social ROI is needed to organize the things. Oracle, Salesforce, and SAP can also be used instead of social ROI. Fourthly, employee performance metrics are required because they are critical for the smooth functioning of an organization. Through this system, we can measure the rate of performance without any personal biasness and preference. An objective and unbiased can automatically improve the industry. Problems can arise in the selection criteria of the employee performance.
It becomes difficult for a company to unlock the true abilities and potentials of data analytics. For instance, for telecommunication companies, it is easier to organize the data but for the smaller industries, it gets complicated to hold big data like gigabytes. Real potentials of the data analytics can be understood by taking in account the personalized view of the data system. To unlock Data, the analytic application like Actuate, Alteryx, Logi Analytics, and Pivotal are used. (Research, 2013)
HOW DATA ANALYSIS CAN EFFECT BUSINESS
Data analytics can affect the working of the industries in many ways. Some of the ways are mentioned below:
By the implementation of data analytics, data will become a valuable thing for the organization. It does not matter that whether a company is big or small. Every company has its data collection. For instance, if the company has a website or a social media page, data will be generated. Big companies that deal with debit cards and credit cards also generate a huge amount of data that needs to be looked after. In short, all business needs a kind of system that will help them to observe, collect, organize, analyzes and interpret data. Companies that have a proper data operating system tends to succeed more as compared to the companies that do not have a data operating system.
Data analytics help to attract more customers because their system is organized and they can cater to the needs of their customers in a very effective manner. Whether you are running a retail store or an automobile business, if your data is arranged you will have a deep insight into your plus points and drawbacks.
It also improves the level of efficiency and operations. If the data is managed the way it should be, it will also contribute to improving the HR department by selecting the right kind of employees. In short, data is main element for the proper functioning of a successful business. (Marr, 2015)
For instance, if data analytics will be used in an apparel industry, their data will come in an organized manner. The owner will get to look at the stats of the company through the data analytics. They will know which product is giving them profit and which one is not working great. In this way, they can increase their profits and control their losses.
Moreover, it will help them to predict that which product will help them to make profits in the coming season. They will come to know how much quantity of the product is needed for sales. It will give them an insight into the requirement and needs of their customers, and they will be able to serve them in a batter way.
References
ciklum. (2015, sep 30). PROS AND CONS OF BIG DATA. Retrieved from www.ciklum.com/: https://www.ciklum.com/pros-and-cons-of-big-data/
Marr, B. (2015). 4 Ways Big Data Will Change Every Business. Retrieved from www.forbes.com: http://www.forbes.com/sites/bernardmarr/2015/09/08/4-ways-big-data-will-change-every-business/2/#5152d0bc71b5
Research, B. H. (2013). The Six Biggest Challenges Facing Big Data and Analytics. Retrieved from bluehillresearch.com: http://bluehillresearch.com/the-six-biggest-challenges-facing-big-data-and-analytics/
ROBERT HANDFIELD. (2013, sep 16). A BRIEF HISTORY OF BIG DATA ANALYTICS. Retrieved from iianalytics.com: http://iianalytics.com/research/a-brief-history-of-big-data-analytics
Rouse, M. (2008). data analytics (DA). Retrieved from earchdatamanagement.techtarget.com: http://searchdatamanagement.techtarget.com/definition/data-analytics
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