For ages, Data has always been the buzzword. As there is a humongous amount of data available in the market it is of no use because it does not benefit the businesses. Whether the data is generated from an individual or generated from large-scale enterprises, in each aspect data needs to be analyzed to benefit individuals or businesses from it. Data Analytics refers to the techniques used to analyze data to enhance productivity and business gain. In the Indian landscape, a data analyst course in Bangalore helps young data aspirants hone their skills, identify their potential, and seek out lucrative employment opportunities after graduation.
A Data Analyst is a professional who can analyze data by applying various tools and techniques and gathering the required insights. The techniques and the tools used vary according to the organization or individual. In India, a data analyst course in Bangalore provides world-class education on data leveraging techniques.
Data analyst course in Bangalore benefits the enterprises by:A data analyst trained from a data analyst course in Bangalore should be able to take a specific question or topic, discuss what the data looks like, and represent that data to relevant stakeholders in the company.
The different types of data analytics for a company depend on its stage of development. Most companies are likely already using some sort of analytics, but it typically only affords insights to make reactive, not proactive, business decisions. More and more, businesses are adopting sophisticated data analytics solutions with machine learning capabilities to make better business decisions and help determine market trends and opportunities. Organizations that do not start to use data analytics with proactive, future-casting capabilities may find business performance lacking because they cannot uncover hidden patterns and gain other insights. Typically, there are four main types of data used in Data Analytics. These are:
Predictive analytics may be the most commonly used category of data analytics. Businesses use predictive analytics to identify trends, correlations, and causation. The category can be further broken down into predictive modeling and statistical modeling; however, it is important to know that the two go hand in hand. For example, an advertising campaign for t-shirts on Facebook could apply predictive analytics to determine how closely the conversion rate correlates with a target audience’s geographic area, income bracket, and interests. From there, predictive modeling could be used to analyze the statistics for two (or more) target audiences and provide possible revenue values for each demographic.
Prescriptive analytics is where AI and big data combine to help predict outcomes and identify
what actions to take. This category of analytics can be further broken down into optimization and random testing. Using advancements in ML, prescriptive analytics can help answer questions such as “What if we try this?” and “What is the best action?” You can test the correct variables and even suggest new variables that offer a higher chance of generating a positive outcome.
Descriptive analytics is the backbone of reporting, it is impossible to have business intelligence (BI) tools and dashboards without it. It addresses basic questions of “how many, when, where, and what.” Descriptive analytics can be further separated into two categories: ad hoc reporting and canned reports.
Post articles and opinions on Professionals UK
to attract new clients and referrals. Feature in newsletters.
Join for free today and upload your articles for new contacts to read and enquire further.