Data quality tools help you identify and resolve problems in your data, either on-premises or in the cloud. They also help eliminate duplicate records and route problems to the appropriate person. Depending on your needs, these tools can help your business achieve its goals. Read on to learn more about these tools and the benefits they offer.

Data quality tools are available on-premises or in the cloud
Data quality tools are software solutions that ensure data is clean and accurate before it is used for analytics. While data is everywhere in the digital landscape, not all of it is ready for analysis. Using data that is inaccurate or incomplete can result in a task taking 10 times longer than it should. Data quality tools are crucial for ensuring that data is fit for analysis, processing, and evaluation.

Off-the-shelf tools are one way to automate data quality processes. These solutions offer a variety of features such as profiling, matching, metadata management, and monitoring. Gartner included 15 providers in its Magic Quadrant for data quality tools. Examples of such tools include IBM InfoSphere Information Server for Data Quality, which offers automated monitoring and data cleansing in batches. It also provides detection of data quality flaws.

The market for data quality tools is moderately fragmented, with several domestic and international vendors offering sophisticated solutions. The intense competition encourages vendors to focus on expanding their reach and building a strong customer base. In the last few years, different providers have been focusing on providing comprehensive solutions. Talend Inc. recently announced that it is releasing Talend Cloud, a cloud-based solution that delivers native integration performance and embedded data quality. It also lets you run integration tasks securely.

When a company wants to use data in analytics, it needs data quality tools that can assess data quality. These tools provide an in-depth analysis and help businesses identify problems in their data. These tools also automate data quality processes, maximizing efficiency while minimizing costs.

They can eliminate duplicate records
One of the biggest problems companies face is duplicate data. This problem can come from a variety of sources and can negatively impact the success of sales and marketing campaigns. Duplicate records are any records that contain the same information as another record. The most visible type of duplicate record is a carbon copy of another record. This type of duplication is the easiest to identify and correct.

Duplicate records are detrimental to operations, because they require expensive and time-consuming removal. However, by using Data quality tools, organizations can eliminate duplicate records automatically. For example, Insycle's 'Merge in Bulk' feature allows companies to reliably merge hundreds of duplicate records with a single click. Another way to detect duplicate records is to use filters.

Manually identifying duplicate records is time-consuming and difficult to perform. It takes weeks to manually go through a database with tens of thousands of records. Furthermore, you risk missing good data or deleting bad data. Therefore, data quality tools are an indispensable part of data quality efforts.

When merging duplicates, you should choose the more complete record. The most updated record is more likely to contain relevant and accurate data. For instance, a master record with a lifecycle stage of 'customer' would be a better choice than a contact with the same name but a different address. By selecting the most complete record, you ensure that your database is 100% accurate.

They can route problems to the right person
Data quality tools are a powerful way to keep your data clean and accurate. They offer built-in rules to prevent errors, and they route problems to the right person. They can also help identify personally identifiable information (PII) such as credit cards, phone numbers, and taxpayer IDs. They can also help you eliminate orphan and duplicate records. They also include strong security features.

If you have data that is duplicated or inaccurate, or if it has missing or incorrect values, it can make it harder to make accurate decisions. It can also lead to frustrated employees and a wasted amount of time and resources. Keeping your data accurate and current is crucial to business success. However, maintaining data integrity haphazardly can lead to ineffective data management, wasted resources, and subpar performance.