What are our data sources?
We use the data sources on the side for ranking solutions and awarding badges in data quality software category. Our data sources in data quality software category include;
Data quality software supports companies in ensuring that their data quality is sufficient enough for the requirements of their business operations, analytics and upcoming initiatives.
Data quality is crucial because higher quality data contributes to better business decisions.
This is especially relevant today because of increased automation. Automated process rely only on data and algorithms to make decisions. Given that modern algorithms increasingly rely on data as well, importance of data quality is increasing.
To achieve data quality goals, data quality software needs to work closely with master data management, data integration and big data solutions of the company.
Data quality is achieved through roles, technology, processes and culture. Important areas in data quality where these software support companies include:
AIMultiple is data driven. Evaluate 162 services based on
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calculated based on objective data.
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The InsideView targeting intelligence platform powers the world's business conversations
The leader in demand orchestration, Integrate's enterprise solution unifies top of funnel demand generation to scale pipeline and accelerate revenue impact.
For 30+ years, Melissa has been helping companies all over the world with solutions to improve the quality of data for a meaningful return on investment.
The Openprise Data Orchestration Platform solves the garbage-in/garbage-out problem to make all your marketing and sales programs more successful.
We use the data sources on the side for ranking solutions and awarding badges in data quality software category. Our data sources in data quality software category include;
review websites
social media websites
search engine data for branded queries
According to the weighted combination of 7 data sources
Segment
InsideView
USPS & International Address Validation Services
Cognism
DemandTools
Taking into account the latest metrics outlined below, these are the current data quality software market leaders. Market leaders are not the overall leaders since market leadership doesn’t take into account growth rate.
Segment
InsideView
Cognism
DemandTools
USPS & International Address Validation Services
These are the number of queries on search engines which include the brand name of the solution. Compared to other Data categories, Data Quality Software is more concentrated in terms of top 3 companies’ share of search queries. Top 3 companies receive 93%, 20% more than the average of search queries in this area.
85 employees work for a typical company in this solution category which is 64 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 88 companies with >10 employees are offering data quality software. Top 3 products are developed by companies with a total of 300k employees. The largest company building data quality software is IBM with more than 300,000 employees.
Taking into account the latest metrics outlined below, these are the fastest growing solutions:
USPS & International Address Validation Services
Segment
InsideView
Cognism
DemandTools
We have analyzed reviews published in the last months. These were published in 4 review platforms as well as vendor websites where the vendor had provided a testimonial from a client whom we could connect to a real person.
These solutions have the best combination of high ratings from reviews and number of reviews when we take into account all their recent reviews.
This data is collected from customer reviews for all Data Quality Software companies. The most positive word describing Data Quality Software is “Easy to use” that is used in 8% of the reviews. The most negative one is “Difficult” with which is used in 3.00% of all the Data Quality Software reviews.
According to customer reviews, most common company size for data quality software customers is 1-50 Employees. Customers with 1-50 Employees make up 34% of data quality software customers. For an average Data solution, customers with 1-50 Employees make up 27% of total customers.
These scores are the average scores collected from customer reviews for all Data Quality Software. Data Quality Software is most positively evaluated in terms of "Customer Service" but falls behind in "Likelihood to Recommend".
This category was searched on average for 315 times per month on search engines in 2022. This number has decreased to 296 in 2023. If we compare with other data solutions, a typical solution was searched 1k times in 2022 and this increased to 1.2k in 2023.
The earlier data quality issues are identified, the easier it is to resolve them. This is because once data is inserted into systems;
Data quality systems allow companies to detect and resolve data quality issues before those changes in data are implemented, reducing cost of data quality issues
Data quality is important for any business process, function or industry that relies on automated decision making systems. Nearly all modern businesses rely on automated decision making systems and data quality software is therefore relevant for almost all modern businesses.
For example, credit scoring and trading systems in finance and recommendation engines in e-commerce are automated decision making systems that are as good as the underlying data.
Data quality issues arise due to improperly formatted, incomplete, incorrect or obsolete data. Data issues arise at the point of observation (e.g. due to faulty hardware), during data communication (e.g. due to issues in the communication channel) or during storage (e.g.overwriting correct data)
Data quality issues can be identified by data quality software as it analyzes existing data, compares data across different tables, databases and systems and compares private data against publicly available data.
Data quality software aims to resolve data quality issues by deleting, modifying or appending records. These can either be done automatically or issues can be highlighted to technical or business personnel.
Data quality software supports companies to measure and improve quality of their data. By acting as a single source of information regarding data quality, these software focus the organization on resolving critical data quality issues