What is Data Analytics?
Data analytics (DA) is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.
It involves examining large and varied sets of data to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.
Types of Data Analytics
3 Types of Data Analytics: Descriptive, Predictive, and Prescriptive. Jeff Bertolucci of Information Week has written a new article about what distinguishes the three types of Big Data analytics: descriptive, predictive, and prescriptive.
HR Analytics and its Applications
The rate at which the business environment is evolving due to digital transformation calls for a more strategic approach to human resource management. Technology is advancing at an unprecedented rate. As organisations become more focused on top line growth and bottom line improvements. There is a growing imperative to redesign, move faster, adapt quickly and learn rapidly.
As it is, organisations have too much data at their disposal, however only a few are using this data to predict the future for their organisations. Using the insights from people data and analytics, HR can strategically transform their business with evidence-based solutions and practice. Leaders & Teams that are affected due to Human Resource processes need to keep an eye on the latest technological and delivery tools & processes such as ERP/HR Systems/Visualization/AI & Machine Learning tools, delivery processes like DEVOPS & Agile are fast becoming essential parts of HR systems.
Question Related to Data Analytics
Why would a customer database be so useful for companies?
We may define database as the structure set of data stored in computer that is available for various processing tasks and ready for query. Many companies make log of customer transaction and information into structured database.
Customer database be useful for companies because:
Get More Customers Coming Back by improving customer experience
We can get more customer satisfactions if we treat them on the way they are special/well known to us
We may use the customer database to trace the trend of purchase and so be able to maintain the inventory
For better customer experience keeping customer information in database for faster access adds easier search mechanism too, that helps improvement in day to day works
For larger companies like Forbes and Kodak there are tremendous amount of information about customer and their day to day transactions. If these companies are not using database for storing information the situation will be same as traveling On Foot to visit the globe rather than taking airways. So it’s apparently impossible to get better customer support, inventory management, trend analysis. Staffing will be another challenge for those companies to manage proper utilization of the manpower.
How can better data management and analytics improve a company’s business performance?
During the course of civilization simple machines improved human living style and later on the combination and improvement on such machines gave rise to highly sophisticated appliances and equipment that eases our day to day tasks.
In the same way the data keeping tasks started from paper based system followed by Spreadsheet. Now this is best supported by database systems.
Database system improve the data management and analytics as:
Better security
Easier to execute search and queries
Relational database system reduced redundancy and enabled linking table so that more space is saved than storing same information on multiple locations
The work performance is improved
Analysis of stored data helped better decision making
The business productivity is uplifted
The examples are Forbes maintained proper data on its individual subscribers and Web sites. Kodak handled 50 million customers compiled from direct purchases and registration from Kodak’s Web site and their photo sharing website.
The online advertisement portal Adsense maintains track of each and every flavor of sites visited by web surfers and feed them ads relevant to their taste. This saves flooding irrelevant ads to customers that are not likely to purchase those item.
Are there any ethical issues raised by mining customer databases?
Data mining is the process of extracting inherent information from the data available in database. When a company traces such personal hidden information then there obviously arise the issue of Breach in customers privacy.
Privacy is the protection against data collection on backside/unknowingly by other person. Using those items to evaluate some one is not permitted.
Other ethical issues arise when some CRM person see a person’s’ shopping history then he may confuse whether to confess customer likes this or that or not. Instead the shopkeeper knows the trend but cannot claim he is right. Moreover the customer might not like backbiting or back side data collection/interpretation.
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