What is Data Analytics: Data Analytics, also known as Data Analysis, is the strategized extraction of business-to-consumer data in both qualitative and quantitative processes to identify trends, both current and future, as well as new opportunities to determine the best decisions for the business which alter according to organizational needs and requirements. This is done for the purpose of categorically identifying and analyzing overall content, layouts, patterns and global trends.
Evolving Role of Data Analytics: Data Analytics has unfolded as a journey because of Data Scientists’ and Data Analysts’ groundbreaking pathway of developing data on trends and such through the compilation of interpersonal or intrapersonal data of social contexts. Over a period of years, Analytics has become multifaceted, with Data Analysts justifying, guiding and prescribing actions for organizations which have allocated capital to develop data analytics in their companies. Organizations are and will be seeking impressive capabilities from data analytics since they have captured and stored massive amounts of data. From governance to choice of new enterprises, this dynamic model has reached a milestone, according to surveys, and will be evolving rapidly in 2018, such as emphasizing more on Data Lakes and thinning down the line between Data Journalists and Data Analysts since both have the imagination and creativity to do either job.
What Kind of Person Should Pursue This: Creativity, the ultimate indicator for being a good Data Analyst, comes from wonder. And wonder is the fundamental requirement for well-researched findings, and to uncover these requires a strong foundation in statistics and the rare curiosity to seek reasons for the assigned phenomenon. Sport is one such area where statistical information is anatomized and debated in thorough discussions. But the range of options or subjects in Data Analytics has no breaking point and no extremity. If you are a person with engaging interests in these, you have come to the right place.
Skills Required and Taught in Certification Training: There are certain technical and business skills and personality traits that are either present in the person choosing this field or acquired through rigorous and healthy self-motivation. Technical skills required are:
1. Programming
2. Database designing
3. Database mining
4. SQL, SPSS, R and/or SAS languages, working knowledge of Hadoop and MapReduce.
Business skills are also required. Not only must you be technical, you must also have the ability to communicate your thoughts. Problem solving, creative thinking and efficient, effective communication are required to be successful in this type of position.
Responsibilities of the Data Analytics Professional: A Data Analyst’s life is multilayered. Responsibilities and work depending upon the level of expertise. An analyst may work as a Data Scientist or Data Analyst, positions which aren’t differentiated by some organizations.
Some duties are:
1. Clean and prune data.
2. Triage code issues.
3. Tackle specific tasks using systems, data sets.
4. Identify new opportunities.
Today’s Data Analysts should be ready for new developments in the field of data analytics and be comfortable presenting discoveries to a conference room full of laymen.
Shalini Madhav
