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Data quality management

Deliver high-quality, clean and trustworthy information with high-quality data that scales regardless of size, format, platform and technology

High quality data means accurate business decisions

Collection, processing and proper use of data it is today the basis for the development of companies. It is thanks to correctly used information that modern enterprises can develop and consolidate their position on a competitive and constantly evolving market.

Data resources used in the company must be reliable and of high quality. This requires proper data arrangement, professional selection and the use of specific information in appropriate situations. The right content allows you to streamline the process in managing the company and in any other activity. Data they also have a huge impact on positive customer relations. Skilful use of data not only attracts new customers, but also makes the consumer regularly use the company's offer, which results in an increase in turnover and real profits of the company.

 

Data quality management it also means creating information security systems, protecting them against unauthorized access. Data security is subject to legal regulations, specifically the introduced GDPR/GDPR regulation. The protection applies primarily to sensitive data that must be properly secured. Data management therefore requires the use of consistent and comprehensive systems and tools that will ensure professional data management, as well as their full security, in accordance with applicable law. Specialized and effective solutions for controlling data quality are products Informatica Data Quality and Brand Governance Informatica Corp. provided by a strategic Polish partner - the company Integral Solutions.

How important is high quality data in the enterprise?

Companies store huge amounts of data, only part of which is valuable and suitable for effective use. High-quality data is key, i.e. those that can actually bring measurable benefits to the company. In today's market, companies have the possibility of dynamic development, which increases their competitiveness. Opportunity for progress comes from efficient data management. Databases are primarily information about customers. Skillful administration of data sets enables effective management of the company and shapes good relations with customers. High-quality datathat are properly used, enable the creation of activities dedicated to the client, which will translate into actual profits and increase the company's efficiency. Appropriate selection and reliable use of resources is a positive consequence of the use of dedicated tools and solutions.

Companies collect more and more data

The development of modern companies is largely possible thanks to efficient use of data. Each unit has its own specific information resources, which should be reliable and of high quality. The amount of data stored in companies' collections is growing every minute. These huge and ever-expanding bases require proper administrative systems. Solutions and tools for data management enable verification and organization of information that will actually be used in the company's operations in order to improve its functioning, and building relationships with clients and contractors.

Restrictive provisions on the protection of personal data resulting from the GDPR / GDPR directive

Company databases contain a large amount of information that requires appropriate protection. Enterprises store information enabling direct contact with the customer. Documented sources are also important the origin of the data.

Very often, these resources contain sensitive data that is subject to special protection. The applicable law requires companies to secure resources and document entities' consents to the processing of information concerning them. The introduced Regulation on the Protection of Personal Data (RODO/GDPR) imposes on entities the rules relating to the methods of storing information about contractors and customers, including potential customers. The data controller is obliged to secure the collections of information that can be used in the manner specified by the GDPR/GDPR directives. Only authorized persons have access to the data. Modern data management systems Informatica meet the requirements of applicable law.

Threats resulting from poor data quality management in the company

Data quality management requires multi-level activities that affect the effective functioning of the company. Incompetent data administration can lead to the occurrence of a number of threats that have a negative impact on many processes. The dangers resulting from poor data quality management in the company are:

  • Loss of potential profit – properly used reliable data leads to an increase in the company's profits. In the event that incorrect data is used, the costs of operational activities increase, which do not bring measurable profits. Thus, revenues are reduced, resulting in a financial loss.
  • Fines for non-compliance with the GDPR/GDPR directive – the current Regulation on the Protection of Personal Data (RODO/GDPR) imposes on companies the rules for securing and processing data. Failure to comply with the regulations may result in a fine or other financial penalties, the amount of which may be up to twenty million Euros or 4% of the company's global turnover.
  • Incorrect business analysis – efficient conduct of specialized analyzes results in increased business efficiency of the company. Acting on data with a low quality index, the company obtains false research results. The effects of incorrect analytics have a negative impact on the business, including poor planning, wrong forecasting and inadequate action.
  • Deterioration of customer relations – the use of reliable and high-quality data makes it possible to build excellent relations between the company and the client. These types of resources allow you to study customer behavior, create a dedicated offer, improve communication and fully respond to consumer needs, which results in a loyal attitude of customers towards the company. Improper data quality management leads to disruption of relations with customers, business partners or suppliers. In the worst case, these relationships may even break off, resulting in financial losses.

What is data quality management?

Running a business efficiently is the result skilful use of data. All existing companies, enterprises and other entities have databases. entitled to data processing users use personal data and other information to carry out the intended activities. If they are of appropriate quality, they improve the internal processes of the entity's functioning, build its image and create excellent relations with the client.

When investing in development, you should constantly acquire new data and skillfully manage their quality, which brings effects in the form of dynamization and expansion of the company's operations, as well as an increase in profits.

Information quality management it is worth starting with an inventory of all resources. The ongoing processes and the systems used so far must be analyzed.

 

Another important action is examining the roles relating to data management. Data quality management is an activity based on the analysis of available information resources. These studies are accompanied by the development and creation of reports on quality of stored and acquired data. An important procedure is the implementation of effective error identification and data correction rules.

 

quality control data cyclical processes. These activities are only possible thanks to implementation of modern solutions and tools, which continuously monitor the resources. These treatments precisely define data owners and qualitative criteria (including qualitative tests). Effective tools for each entity are the Data Quality and Governance products of the brand Informatica. Solutions offered by Integral Solutions – partner Informatica Corp. – are implemented by the best specialists in the IT industry. Systems Informatica is a guarantee of effective and professional data quality management.

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