Data Analytics - Explained
What is Data Analytics?
If you still have questions or prefer to get help directly from an agent, please submit a request.
We’ll get back to you as soon as possible.
- Marketing, Advertising, Sales & PR
- Accounting, Taxation, and Reporting
- Professionalism & Career Development
Law, Transactions, & Risk Management
Government, Legal System, Administrative Law, & Constitutional Law Legal Disputes - Civil & Criminal Law Agency Law HR, Employment, Labor, & Discrimination Business Entities, Corporate Governance & Ownership Business Transactions, Antitrust, & Securities Law Real Estate, Personal, & Intellectual Property Commercial Law: Contract, Payments, Security Interests, & Bankruptcy Consumer Protection Insurance & Risk Management Immigration Law Environmental Protection Law Inheritance, Estates, and Trusts
- Business Management & Operations
- Economics, Finance, & Analytics
Table of ContentsWhat is Data Analytics?How is Data Analytics Used? Why Data Analytics MattersAcademic Research on Data Analytics
What is Data Analytics?
Data analytics is a process of extracting valuable insights from raw data that are needed to arrive at conclusions about an information. This is a holistic process that involves extracting, cleansing and inspecting raw data with the aim of gathering relevant information that are essential for decision making. There are a number of techniques used in data analytics and these have been summed up into processes that help analyze raw materials for the purpose of decision making. Systems and businesses use data analytics to enhance the organization and efficiency of the business or system.
How is Data Analytics Used?
All categories of data analysis are subsumed into data analytics. Both quantitative and qualitative approaches can be used for data analytics with the aim of extracting relevant information and insights needed for decision making. In order to extract or discover useful information that facilitate improvement in a company or business, raw materials might be subjected to cleansing and transformation of raw materials to improve the efficiency of a system. For instance, manufacturing companies use data analytics to identify bottlenecks in the manufacturing process, content-based companies also use data analytics to reorganize and align their contents to suit the needs of their clients and improve productivity. Data analytics involve certain processes and steps, they include the following;
- Know how the raw data to be analysed is grouped. For example, data groupings might be based on gender, product category, demography, and price. Also, a raw data can be grouped alphabetically or numerically.
- Once the data grouping is identified, collection of data is the next process. There are a number of ways to collect data.
- Organization and analysis of the collected data is the next step.
- After the data are organized and analysed, they must be thoroughly cleaned. A cleanup process must be initiated.
Here are some important things you should know about data analytics;
- All types of data analysis is regarded as data analytics.
- It is a process of analyzing raw data in order to extract relevant information that are needed for decision making.
- Processes and techniques used for data analytics have been transformed into mechanical processes and algorithms.
- A better performance and efficiency of a business or system is enhanced through an effective data analytics.
Why Data Analytics Matters
Oftentimes, people wonder why data analytics really matter in a business or organization. Through data analytics, the raw materials that provide evidence on how a business of being operated is analyzed, organized and cleaned to extract information relevant for making decisions in the company. Data analytics is an effective way of optimizing the performance of a business and this is essential for its growth. Data analytics helps the management of an organization or business make important business decisions. This will in turn increase the efficiency of the organization. There are four major types of data analytics, they are;
- Diagnostic analytics: This type of data analytics is based on finding the reason why something happened. Such as whether the sales of a company is affected by a factor or the other.
- Predictive analytics: This is analyzing a business based on occurrences that are likely to happen in the nearest future. This method of analysis is based on pure predictions that something is likely to happen in an organization.
- Descriptive analytics: this type of analytics basically describes an event that happened at a given time. It describes certain occurrences in business.
- Prescriptive analytics: this form analytics prescribes remedies or appropriate measures that can enhance the efficiency of an organization.
Although, data analytics can be used across many industries, it is rampantly used in the travel industry, business industry, among others. It can also be used as a measure to optimize the performance of a company across many industries. The method allows a company gather raw data, analyze the data, organize them so as to extract relevant information useful for decision making. Also, business trends are identified and analyzed using the data analytics processes. This will improve the efficiency of a business, as well as profits.
Academic Research on Data Analytics