What is Data Analytics: Data Analytics, also known as Data Analysis, is the strategic 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 changing business according to organizational needs and requirements. This is done with the aim of categorically identifying and analyzing the overall content, layout, patterns and global trends.
Developing role for data analysis: Data Analytics has emerged as a journey through the pioneering path of Data Scientists and Data Analysts to develop data on trends and such through compiling interpersonal or intrapersonal data in social contexts. Over a number of years, Analytics has become multifaceted, with data analysts justifying, guiding and prescribing actions for organizations that have allocated capital to develop data analytics in their businesses. Organizations seek and will seek impressive opportunities from data analytics as they have captured and stored large amounts of data. From managing to selecting new businesses, this dynamic model has reached a milestone according to studies and will evolve rapidly in 2018, such as emphasizing more on Data Lakes and fading the line between Data Journalists and Data Analysts as both have the imagination and creativity to execute both jobs.
What type of person should pursue this: Creativity, the ultimate indicator of being a good data analyst, comes from wonder. And wonder is the basic requirement for well-researched findings, and to reveal these requires a strong foundation in statistics and the rare curiosity to seek reasons for the assigned phenomenon. Sports is one such area where statistical information is anatomized and discussed in thorough discussions. But the range of settings or topics in Data Analytics has no breaking point and no extremes. If you are a person with engaging interests in these, you have come to the right place.
Requirements and teaching skills 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:
2. Database design
3. Database mining
4. SQL, SPSS, R and / or SAS languages, working knowledge of Hadoop and MapReduce.
Business skills are also required. Not only do you need to be technical, you also need to have the ability to communicate your thoughts. Problem solving, creative thinking and effective, efficient communication are required to succeed in this type of position.
Responsibility of Data Analytics Professional: The life of a data analyst is multilayered. Responsibility and work depending on the level of expertise. An analyst can work as a Data Scientist or Data Analyst, positions that are not differentiated by some organizations.
Some tasks are:
1. Clean and crop data.
2. Triage code issues.
3. tackle specific tasks using systems, datasets.
4. Identify new opportunities.
Today’s data analysts must be ready for new developments in data analytics and be comfortable presenting discoveries to a conference room full of lay people.