Data analytics is a fast-growing field with the potential to transform businesses of all sizes. According to the American Internet Council, data analytics will become a $170 billion sector by 2020. Since data analytics involves identifying trends in large sets of data, it’s a perfect fit for an era when almost every business stores and analyzes massive amounts of information digitally. Data Analytics refers to the use of statistical techniques and processes to find insights in data and convert them into actionable information. It helps businesses understand their customers better and make informed decisions on how best to serve them.
What is Data Analytics?
Data analytics is a method of extracting meaningful insights from data to help companies make better business decisions. It is a process that can be applied to any type of data, whether structured or unstructured, to generate insights that can inform your business decision-making. Data analytics can be used to gain insight into customer behaviour, marketing effectiveness, sales performance, product demand, supply chain issues, and more. Additionally, data analytics can be applied to both structured data (data that is organized in a way that computers can read and understand it, like numbers in a spreadsheet) and unstructured data (data that is not easily readable by computers, like a transcript of a voicemail or a tweet). Data analytics can be used to draw insights from all of these types of data.
Importance of Data Analytics
Data Analytics is a process used to find insights in large amounts of data and make informed decisions based on the insights discovered. It is an important part of almost every organization because it helps them to understand their customers better and give them a better experience. In order to do that, business needs to have some information about what type of customers they have, how they behave and what they want. Data analytics helps to gather data and process it to get some information so that company can make decisions based on this information. It can be a simple decision like what to offer next to a customer or a big decision like where to open next office.
Types of Data Analysis
Quantitative Analysis - It is the process of working with structured data to draw conclusions that are primarily based on numbers. It is a widely used method of data analytics that can include a wide range of statistical techniques, such as frequency analysis, hypothesis testing, and regression analysis.
Qualitative Analysis - It is an analysis of unstructured data to determine patterns and draw conclusions about human behaviour and attitudes. In marketing, qualitative analysis is often used to understand customer needs and motivations, which can then be applied to quantitative analysis to conclude data.
Steps to follow for effective data analytics
- Define the Problem - The first step before you start your data analysis is to define the problem. As we mentioned above, the data analytics software can be applied to different fields, so it’s important to decide what exactly you need. For example, you may have to research how many customers you have each week, how much money they spend, how often they buy a product, etc. - Set up your Data Source - There are two ways to get your data. You can manually enter it into the database or use an automated feed. The feed is more convenient, but it takes some time to set up. The best way to get data is to use a database, like Microsoft Excel or Google Sheets. - Choose the right Data Analytics Software - Every business has different needs, and it’s important to choose the right software to meet them. When you don’t know which software to use, you are most likely to fail, and that’s why we built this guide. - Prepare your Data - Once you have chosen the software, prepare your data for analysis. This means organizing the data and cleaning it up to ensure it is ready for analysis. Organizing data often means sorting it into categories and putting it in order. Cleaning data means removing any erroneous data that is incorrect or incomplete. - Run the Analysis - Now it’s showtime. Start running the analysis to get some useful insights. - Analyze the Results - After you finish running the analysis, review the results and draw your conclusions. - Create a Report - Now that you’ve got the results, you are ready to create a report. A report is a written summary of your data analysis. It is almost always necessary to include charts and graphs in your report. - Present your Data Analysis - Once you’re done with the report, it’s time to present your data analysis to your team members or your clients. You can do it in person, give them a written report or just send them the graphs. - Use the Results to Make Strategic Decisions - Once you’ve presented the data analysis, it’s time to make strategic decisions based on the results and use them to further grow your business.
Bottom line
Data Analytics is a process of identifying patterns and trends in data to make better decisions. It can be applied to both structured and unstructured data, and it can be used to generate insights on a wide range of topics. To be effective, it’s important to define the problem, set up your data source, choose the right data analytics software, prepare your data, run the analysis, analyze the results, create a report, present your data analysis, and use the results to make strategic decisions.
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