Types of Data Analyst & The Difference between Data Analyst & Data Scientists
Data Analyst & Data Scientists are the two upcoming jobs in 2021. Before discussing the data Scientist and data analyst lets the about the Python and its usability. Data Analyst & Data Scientists will be the highest paid job in the coming years.
In every firm, company or large business establishment’s large amount of data is stored. Day by day these industries heavily rely on these data to make future decisions. If any company is launching any product in the market they research on huge data. like which market is better in the current scenario. The product to launch, how much investment is to make and the number of customers to target with the available investment. They also make a decision like the per cent of profit or loss they will suffer.
Data Analyst & Data Scientists are the two upcoming jobs in 2021.
The data analyst plays a very important role in these companies. It is because they provide a digital numeric value to the available data in the company. It’s easier to take decisions to on different business functions and performance of the department. The data analyst provides the numeric value to these data. Once a value is added to any data it becomes information.
According to the research done by a reputed company in coming years the data analyst job will be in the high demand. Nearly thirty lakh data analyst job will be available in the market around 2021. One can take a master degree and training in Python or other languages which supports data analysis. You can take a look at the interview related question and answers to crack the corporate interview depending on your skill level.
If the role of a data analyst sounds like a good fit for you, here’s what you need to know.
Data Analyst & Data Scientists are the two upcoming jobs in 2021.
The various kinds of Data Analytics
There are four ways in which we can categorize data analytics. These four types of data analytics bring value to a company and organization.
Descriptive analytics- Descriptive analytics research what happened in history. Descriptive analytics reads about the historical. It checks the revenue of each month, sales in each quarter, the web traffic. These types of data spot the trends in an organization.
Diagnostic analytics – The diagnostic analytics checks why it happened by comparing and analyzing descriptive data sets. diagnostic analytics to get the dependencies and flow pattern trends. The diagnostic analytics helps an organization determine the reason of plus or minus trends or outcome.
Predictive analytics – Predictive analytics seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analyses. This is the reason which allows an organization to take charge for the upcoming customer. Predictive analytics is very important for reaching out to a client who is unlikely to renew a contract.
Prescriptive analytics – The prescriptive analytics identifies the kind of action one can take in business. This analysis adds tremendous value in addressing the industry problems or stay ahead of the trends. This kindly of analytics requires using the complex algorithms. Prescriptive analytics shows the large information easily.