To succeed in business, you need to use quality data. Thanks to which they will become a key factor, it will be possible to develop quickly and increase profits.
To become the owner of such information is quite simple. To do this, you should conduct data analytics (DA). This process requires the right approach to work and the study of all its aspects.
Data analytics and its use cases
Data analytics is a process that involves the collection of information, it’s processing, and adaptation for further use. The results of such work become the basis for forming reports on the current situation and creating forecasts for the future.
Analytics is a standard process in demand in various fields of activity. In addition to business, it is used daily without even noticing it. In the process of data analysis, manual and automatic methods, as well as a variety of algorithms, are used. All this helps to clean up the information from any shortcomings and prepare it for customers’ needs.
Types of analytics
In their work, experts use four methods of data analysis. Each provides specific actions and allows you to get one or another result. By combining different types, analysts get the desired effect.
Types of DA:
- Descriptive. This type of analysis is the simplest. It provides for obtaining data about a specific event for a particular period. Descriptive analytics uses aggregation and mining. The first is the collection of data and grouping them into different groups with similar characteristics, and the second is the search for helpful information. Aggregation is the initial stage of analysis. After that, the required data is extracted from the standard array. The work results are combined into a common database and transferred to the customer in a form adapted for ordinary people.
- Diagnostic. Such analytics is deeper than descriptive. It is a three-stage procedure that allows you to obtain information that explains an event or answers a specific question. The first step in the analysis is to look for anomalies. They are detected quickly enough, so this stage cannot be called difficult. After that, the specialist finds additional information that helps to establish the cause of the anomalies. In the final step, the analyst determines the consequences that the detected abnormality can lead to.
- Predictive. The most popular type of analysis is predictive. It is used to plan further steps for business development and helps to predict future profits, the number of new customers, sales volumes, and much more.
- Prescriptive. The most complex type of analytics is considered rigid. It is used as a complement to predictive, as it is based on its final data. The complexity of the research and all the costs of its implementation are not commensurate with the benefits received.
Stages of analytics
Optimizing data quality is a complex process. It consists of many stages, each of which data manipulations are carried out. If the standard sequence of actions is followed correctly, it will be possible to achieve the desired result and obtain valuable information at the output.
Step by step:
- The beginning of DA is the definition of information requirements. They are selected by the customer depending on the tasks that need to be solved using high-quality data.
- Next, the method of presenting information is selected. This is important to speed up further work, as specialists or the software used will ignore data of a particular type. In this case, attention will be paid to numerical data, and text data will be ignored.
- The third step is to collect information. This process takes much time, as it requires studying a vast amount of materials. The necessary data is searched by viewing various paper and electronic sources, analyzing the results of questioning people, and processing photos and videos.
- All collected information is subjected to a systematization procedure. It will simplify further analysis and minimize the time spent. Most often, systematization is carried out using special programs. They sort all the data according to specific parameters and then form separate categories, tables, and more.
- At this stage, the data is cleaned. They are checked for compliance with the specified criteria, and various problems are eliminated. The latter include the presence of a large number of errors, duplicates, contradictions, and anomalies.
- Prepared information goes to analysts. They, on their own or with the help of software, tailor the data to the needs of the business. The work results are transferred to the customer, who uses high-quality information to achieve his goals.
Accurate and reliable information was valued at all times. Nowadays, it has become one of the main capitals of any company. To obtain it, data analytics is used. It is a set of measures aimed at cleaning information from everything superfluous. If you organize the process correctly, you will achieve the ideal data quality that can be used to obtain a particular benefit.