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Today, information is one of the main assets of any company. It is used for the business’ benefit development, bypassing competitors, and increasing profits. All data used must necessarily meet the essential criteria. Only in this way will they benefit their owners and not contradict the definition of quality data.

Information analysis and engineering

High competition in every area of ​​business leads to companies constantly looking for ways to improve their work and approach to communicating with customers. Data engineering is an essential tool that helps achieve success in this matter. It provides for collecting and filtering all incoming information to improve its quality. The result of the work is carefully verified information that can be safely used to meet the company’s needs.

People and special software carry out the analysis of the collected information. Their joint work makes it possible to form vast amounts of data, which can later be customized to the needs of a particular company. Such work provides complete data QA and makes the information usable. In the future, the business will use the sorted data for its own needs, creating on its basis a variety of reports on the current situation in the market and making plans for several years ahead.

Global automation affects different areas of activity, including data QA. With the help of modern programs, it is possible to cope with the tasks and achieve the expected results quickly. The applications are used to minimize the impact of the human factor on the final quality of information. In addition, they do the work in a few minutes, which people would need for several days or weeks.

Data QA options

Not all available information is of high quality. To be considered as such, it must meet eight key parameters. Each of them discards certain information, leaving only the most valuable data.

Key parameters:

Uniqueness. It is essential for business, so sorting data is carried out according to this criterion. Using the uniqueness check, you can exclude many repetitive pieces of information that have fallen into a standard array from different sources.

Timeliness. Everything has its time. This expression is also applicable to arrays of information. Data that meets this criterion must be up-to-date. If they are outdated, then the benefits of the information received will be minimal.

Accuracy. Data that reflects the actual situation is considered to be accurate. Many people think this evaluation criterion is the key and use it in 99% of cases when analyzing large amounts of information. It allows you to reject information that has at least some inconsistencies.

Relevance. Companies always have precise requirements for the quality of information. Therefore, in the analysis, experts use such an important criterion as relevance. It characterizes the ability of data to meet business needs and not affect “neighboring” areas.

Interconnectedness. Sorting by this parameter is not always used. This is due to the specificity of the criterion, which is suitable only for some cases. Relationship refers to the existence of links between information from different sources. This property allows you to transfer data from one array to another, knowing exactly where it should be placed.

Completeness. It is essential to get a complete picture of a particular event. Totality is understood as the absence of specific arrays of information gaps that cannot be filled with missing data. This criterion is the key in many cases, and various information collections are formed around it.

Consistency. For data scientists, inconsistencies are often the worst-case scenario. Because of them, it is necessary to double-check large amounts of information and find inconsistencies. The latter reduces the data quality as much as possible, so their presence in the array is unacceptable.

Reliability. This criterion is understood as the simultaneous completeness and accuracy of the data. Both properties are essential for information analysis; therefore, the reliability indicator is rarely neglected.

Why use qualitative data?

By owning high-quality data, the company receives many benefits. You can use them for your help, increasing the business’s profitability and reducing the likelihood of problems.

Privileges from operating with high-quality information:

Making the right decisions. Carefully selected information is a real treasure for any company. With its help, it can correctly assess the current situation, predict possible financial losses and calculate potential income. All this guarantees complete awareness of any issue and ensures the right decisions are made.

Ease of determining the target audience. In modern society, there are people with radically different views on life. This leads to significant difficulties in choosing the optimal range of products or services that would satisfy the needs of most customers. In this regard, the selection of the target audience is carried out, which makes it possible to understand the categories of people who are most interested in the product or service of the company. It will become much easier if specialists operate with carefully sorted data. This approach will speed up the work and help you quickly adjust the business to the requirements of most customers.

Expansion of the client base. All companies, regardless of their activity, dream of getting more customers. To do this, they carry out various promotional activities and analyze in detail any incoming information about the requests and desires of people. If it is of high quality, then the business can quickly change its approach to its activities and adapt to potential customers. Such measures will inevitably lead to an increase in the number of new buyers or customers of services.

The advantage over competing firms. Every business needs competition. It helps to develop to bypass other firms. For customers, competition will also be a positive thing. It will expand the range of goods or services and significantly reduce their cost. Companies are the only ones hurt by competition. They lose part of the profits and lose many customers. To stay ahead of their business peers, firms need to use data that has passed all stages of quality control. Thanks to them, it will be possible to quickly find problematic issues and solve them as soon as possible. In addition, this approach will help to adapt the business to new realities instantly.

Reputational privileges. The most valuable asset a company has is its reputation. They value it and try in every way to improve it. You can achieve the desired effect with good quality data. They will open access to new opportunities and analysis of the current situation. All this will help eliminate various shortcomings, determine people’s opinions about a particular action, and find positive aspects, the influence of which should be strengthened. The correct use of such information will give a chance to reduce reputational losses and increase people’s trust in the firm.

Economic advantages. The complex of all the privileges listed above gives the business the most crucial plus – economic benefits. It is formed by increasing the client base, growing reputation, effectively fighting competitors, and making the right decisions. All this also reduces the risk of rash actions that can negatively affect the company’s income.

Data QA is a set of measures to clean up a standard array of unnecessary information garbage. This process is mandatory for owners of large and medium-sized businesses. It provides companies with the broadest possible opportunities for further improvement and increased profits.