Data Integrity Software maintain information as it was inputted.Sometimes information in the database may end up corrupted by some unauthorised persons.

The Data integrity software will protect these information from being tempered. Corrupt or tempered data end up annoying customers or even business partners.Apart from using internet security software, you can invest in data integrity software.

When data flows are clean, there is productivity and an increase in revenue for your business. Data Integrity software helps in different aspects.

These includes data cleansing, data integration,data automation and data management.

The role of these tools is to identify errors by the use of algorithms, lookup tables and help tackle various activities such as protecting contact information and mailing address, performing data mapping among other errors that might be encountered during the process.

Data Integrity Software use AI Software Development Tools to detect some of these errors.

For example, when someone tries to edit or delete some important information, the software will give an Alert to the authorized persons.

What to consider when selecting Data Integrity Software.

There are some aspects to consider when you want to select the Data Integrity Software for your business.

You need to put in mind what your business prospects are and what a particular tool can do to enhance your business productivity.

You should strategise and ensure that the integrity tool you settle for is capable of doing away with all the problems that data corruption entails while at the same time being pocket friendly.

There are as follows;

Identify your data challenges.

You need to focus on issues that pertain to incorrect data, duplicated data, missing data, and all other issues that are related to the collection that can make all your business issues take a backward trend.

This will enable you to select the best Data Integrity Software that suits your challenges.

Not all tools can solve your business problems holistically. You need to revisit the whole data problem and examine it and put focus on the tools that you are currently using to see if they are truly delivering.

They will help you know what can be changed in the way the organization is managing and storing data.

Have an overview of the strengths and weaknesses of the Data Integrity Software at your disposal.

All tools offer services based on their strengths and weaknesses. Some tools are specially created to provide specific applications that aren’t provided by other solutions. Some data cleansing tools are good at spotting errors, which is their specialty.

Some handle the issue of IoT data while some are good at pulling together disparate data types and formats. You should be in a position to understand how exactly a data cleansing tool works and how it works in terms of automation.

There are other factors that you should also put in mind. These include issues that are related to data controls and licensing costs that are significant when it comes to the data tools that you use.

-Data cleansing feature.

A Data Integrity Software should helps to fix all the incorrectly formatted, incomplete, or irrelevant data that appears in a dataset.

These tools ensure that the incorrect data doesn’t have the chance to enter the database by either removing it altogether or making corrections by transforming it before it finds its way into the database.

Data enrichment solutions.

These are Data Integrity Software that bring forth additional data from other sources to make the data complete and updated.

It’s especially important for the sales department because it makes the available information up to date to be at par with the changing customer affiliations and trends.

Data validation services and automation.

Organizations use data validation tools to make sure that. when data is transferred, it does not get lost.

The volume of data transfer in big organizations is big and therefore you can’t depend on manual ways to validate the data.

You have to use data validation tools to cross-check input data against source data.

Data governance aspect.

Data governance organizations help organizations in terms of security and storage of data in a central place.

They can also automate audits and improve workflows. There is also data catalogs which is a well-established inventory of data assets. It ensures that information is readily available when needed.

Data quality platforms feature.

These are the central points where data quality is managed in its whole existence. The tools coordinate different issues ranging from cleansing, metadata management and enrichment processes.

They also offer a complete view of data quality metrics and can tell where areas of concern are. All the different data quality tools have different approaches to the way they execute their tasks.

Data integrity risks.

Different factors can affect the integrity of data that has been stored in a database. These factors include:

Human error.

There are Data integrity risk occur situations when people incorrectly enter information. Sometimes they delete data or even duplicate it.

There are occurrences when the simple protocol is not followed when entering data and that leads to integrity risks because the information that is entered does not conform to the data that is expected.

Sometimes there is an issue with data transfer whereby data information is present in one destination but not present in a relational database.

Bugs and viruses.

Some viruses are pieces of software that can incapacitate the validity of data causing Data integrity risks. They can invade a computer and compromise data.

They do so by tampering with how the hardware works and in so doing render data incomplete or totally eliminated which makes the information irrelevant and hard to use.

How to avoid data integrity risks.

Data integrity risks can be eliminated when some actions are put in place. Some precautions include :

-Have only authorized people to have access to the data.

-Ensure that the data collected is correct and when used it’s the same correct data.

-Ensure that you backup your data all the time.

-Making use of logs to ensure that when data is added or deleted, the records are up to date.

-Conduct and having regular internal audits.

-Put in place error detection software to help you note where errors occur.

Do you have data integrity issues?


Retrievability and accessibility

Accurate data needs to be in the proper locations and at the right time when it’s needed. It helps in the forward coordinations of business projects in terms of presentations and deals.


Traceability

You need to ensure that data gives you access to trace every touch point that you make with a prospect or customer.

Data needs to inform those at the front of running the business of the foreseeable shortcomings. The touchpoints have to be accurate for the business to progress.

Reliability

Your data has to give you information that is reliable if it has to make you great in decision making that pertains to the business prosperity. That is how reliable the business data should be.

How to preserve data integrity.

There are issues in data integrity that bring forth the need to preserve data security. Here are ways of preserving data security:

Validate input

Data is supplied by either known or unknown sources. Some of the unknown sources include an end user, another application, or just a malicious user.

You need to validate the input to make sure the data is verified and good for your system and business endeavors.

Validate data.

You should also make sure that your data processes haven’t been corrupted and all the principles of the organization are adhered to in the data that flows in your channel.

Eradicate duplicate files.

Some information has the tendency to get into unwarranted spreadsheets, emails or shared folders. It can therefore get into the hands of employees who don’t have access to the information.

It’s important that such files are cleaned or removed from the system before they get their way into such folders.

Data backup.

There are occurrences of data loss when organizations get hit by ransomware attacks. It’s therefore advisable that you backup your data to prevent permanent loss that definitely affects data integrity. i

Access controls.

There are situations whereby individuals within an organization trace their way into data without permission.

These are individuals that shouldn’t have access to the information. In some cases, outsiders who masquerade as insiders can also try to gain access to the data.

There is a need to implement a privilege model that ensures that only those users allowed to have access to the data can get it.

Keeping an audit trail.

Data integrity has a way of tracking down the source of any data breach. This importance can’t be overlooked because it provides an organization with the leads to the source of the problem as well as how it can be handled.

An audit trail has the following elements:

  • It is automatically generated.
  • The users should not have access to or the ability to tamper with the audit trail.
  • There is a record of every event. This includes creation, delete, reading, or modification of data.
  • All the events are aligned to the user and therefore all the occurrences are subjected to someone.
  • There is the time factor during every event and therefore every activity is known when it exactly occurred.

TOP DATA INTEGRITY TOOLS.

1.Cloudingo.

This Data Integrity Software is a data cleansing tool that is designed for Salesforce. It does, among other things, handling issues that pertain to data migration as well as spotting data inconsistencies and other errors that are human-related.

It has strong security control and is flexible and controls data imports. 

Key features 

-It’s drag-and-drop interface makes the user do away with coding and spreadsheets. It also has templates with built-in analytics and allows customization.

The issue of representation state transfer(REST) and simple object access protocol(SOAP) are supported by the APIs of the app. It’s therefore possible to run the application from either cloud or an internal system. 

-It’s possible to merge duplicate records and convert leads to contacts, as well as deduplicate record files using the data cleansing management tool.

This tool also ensures that stale records are deleted appropriately, tasks are automated as expected and change tracking records are presented. There’s also a near-time synchronization of data by the tool. 

-There are strong security controls that include permission-based logins and simultaneous logins. The user accounts and tools that audit who has made changes are also made available here. 

2.Data ladder.

This Data Integrity Software has the ability to standardize and prepare data. It integrates, links, and matches data from all the possible sources and also taps several algorithms that help identify some probes such as domain-specific issues and abbreviations. 

Key features.

-The tool supports integrations by use of a combination of databases, file formats, big data lakes, enterprise applications, and social media. The templates provided by the tool necessitate cleansing and managing data sources. 

-There are data standardization features that bring in more than 300,000 built-in rules as well as allow customization. There is the proprietary built-in recognition and its system allows organizations to build their RegEx-based patterns visually. 

-The data-match enterprise solution uses multi-threaded and in-memory processing to boost speed and accuracy and also supports unstructured data. 

3.IBM(infosphere Qualitystage).

This Data Integrity Software offers a broad approach to data management. It offers both on-premise and in-the-cloud provisions.

It’s designed for big data, business intelligence, data warehousing, application management, and master card management which makes it ideal for businesses. 

Key features 

-It provides a deep data profiling tool that makes users understand content quality and other issues such as the structure of tables, files, and much more.

There’s also a provision of machine learning that can auto-tag data and identify other significant issues that affect the data format. 

-The arrival of bad data is managed by more than 200 built-in data quality rules. These tools connect the problem to the root cause hence enabling an approach to solving the problem. 

-There is a data classification feature that brings to the fore personally identifiable information(PII) that has information that includes taxpayer issues, IDs, credit cards, phone numbers, and all the relevant information about a person.

This feature also enhances the elimination of duplicate records or data that can end up in unwarranted hands. 

-This platform also supports strong governance due to the strong security features available. 

4. Informatica.

Informatica Data Integrity software deals with data management which includes rule-based capabilities, exception management and artificial intelligence insights.

Futhermore, it offers a modular MDM solution that provides a single view of data.This software allow users to create an authoritative view of business critical data from duplicate, disparate and conflicting sources.

It also features machine learning and AI to perform data quality, data integration, business process management and data security functionalities.

Key features 

Qualifies in issues of validation, data enrichment, standardization, and consultation of data. It offers versions that can stay on the cloud or also on Microsoft Azure and AWS. 

-The application of Master Data Management helps in dealing with data integrity using the processes of matching and modeling. It also does data cleansing and automates data profiling, discovery, and matching all from a central position. 

-The MDM tool also supports different kinds of structured and unstructured data that have applications, legacy systems, profile data, third-party online data, and other data issues like IoT and interaction data. 

5. OpenRefine.

This is a free open-source Data Integrity Software that can be used for managing, manipulating, and cleansing data. It was formerly known as Google Refine.

It can cleanse, manage, and manipulate data and is capable of accommodating up to a few hundred rows of data.

It also enhances disparate data and is available in several languages that include English, Chinese, Spanish, French, Italian, Japanese, and German. 

Key features.

-The web, social media data, and other standard applications help this solution clean and transform data. 

-It has powerful editing tools that help in removing formatting, filtering data, and changing enormous data to fit appropriate requirements. 

-It has tools that can reconcile and match different data sets that make it possible to obtain, cleanse, and format data for web services, websites, and other database formats.

This tool also has a provision for numerous extensions and plugins that can work with many data sources and data formats. 

6. SAS(Data management).

This tool has powerful tools for managing data and also metadata management, ETL and ELT.

It also assists in migration and synchronization issues as well as a data loader for Hadoop. There’s also a metadata bridge that can handle big data. It’s a role-based graphical environment tool. 

Key features 

-There is a powerful set of functionalities that enhances data quality management. These tools make it possible for data integration, process design, metadata management, data quality controls, ETL and ELT, data governance, and issues that deal with data migration to take place smoothly. 

-It also has strong metadata management capabilities that can assist in maintaining accurate data.

These tools ensure that there is data validation and that the metadata import and export column is in place. There are also standardization capabilities that make sure data integrity is kept at the highest possible level. 

-There is also support for reusable data quality business rules that qualifies data quality into batches, near-time, and real-time processes. This helps the business fraternity to get data at the most appropriate and convenient time. 

-There is also a provision for native language awareness and location for 38 different regions worldwide. 

7. Precisely.

When precisely purchased Trillium, it made great heights in data integrity space. Precisely offers five versions of the plug-and-play application.

There are Trillium Quality fit Dynamics, Trillium Quality fit Big data, Trillium DQ, Trillium Global Locator, and Trillium Cloud.

They do address different tasks with the same objective of optimizing and making integration of accurate data into the system. 

Key features 

Trillium Quality for Big Data helps in cleansing and optimizing data lakes. Machine learning and analytics within its reach spot all the irrelevant information in the data and eradicate it. It also takes care of incomplete information while helping to deliver data. 

Trillium DQ helps in finding missing, duplicate, and inaccurate information in the data set. It also assists in uncovering relationships within households, businesses, and accounts as well as adding missing postal information, latitude, and longitude data to make the information complete and relevant. 

Trillium Cloud is mostly associated with quality issues for private, public, and hybrid cloud platforms and applications. The issues that are dealt with include cleansing, matching, and unifying data from all data sources and domains. 

8. Talend.

The framework that Talend uses includes machine learning, pre-built connector and components, data governance, and management and monitoring tools that help in ensuring that data is clean and reliable.

This Data Integrity Software deals with validation, standardization, as well as duplication of data. It also offers on-premise and cloud-based applications while ensuring that PII and other sensitive data are protected. 

Key features 

-The graphical interface and drill down offer the capabilities to display details about the integrity of the data and also helps the user to evaluate the integrity of the data in the database and measure performance against internal and external metrics as we as standards. 

-There is a provision for automatic data quality error resolution that happens through enrichment, harmonization of data, and deduplication. 

Talend has four different versions of software. There exist two open-source versions that just provide basic tools and another advanced model which is a subscription model.

This model has strategic and robust functionalities of data mapping, reusable ‘jobless’, and interactive data viewers. The paid data management platform offers more advanced cleansing and semantic functionalities. 

9. TIBC. 

This Data Integrity Software is mostly inclined towards analyzing and cleansing relatively large volumes of data and ensures that the end product is rich and accurate data sets. There are either on-premise or cloud versions available.

The tools presented by this platform help in profiling, validating, standardizing, transforming, cleansing, and deduplicating all the available data sources and file types. 

Key features.

-The deduplication engine available supports data-based searches that help to find duplicate records and data. The search engine is of a highly customizable level and can deploy match strategies based on areas such as multiple languages.

There is also an offer of reduplication against a dataset or any kind of external master table. 

-This platform also allows users to analyze and regroup data by flagging empty rows, and text patterns, and making cleaning of data simple by providing a high level of flexibility in the way it offers its services. 

-The platform has strong editing functions that help users to manage columns, cells, and tables by filling and clustering cells. 

-Also present is the address cleansing function that works in cohorts with TIBCO GeoAnalytics, as well as Google, maps to help ensure that data integrity is maintained. 

10. Validity.

Validity Data Integrity Software, which works with DemandTools, has an enviable collection of tools specifically designed to manage CRM data within Salesforce.

The solution can accommodate large data sets and deduplicate data within any provided database table.

It can also perform multi-table mass manipulations and also make inputs into Salesforce objects and data manipulations and standardization. Validity solution has, within it, powerful automation tools that help in the enhancement of data quality. 

Key features.

-DemandTools/Validity is capable of comparing a variety of internal and external data sources and also merge, deduplicate and maintain data. 

-DemandTools has many powerful tools that can reassign ownership of data. There’s also the Report Module that allows users to pull external data into an application and help compare it with any data inside a Salesforce project. 

Validity JobBuilder tool which automated data cleansing and maintenance tasks by merging duplicates, backing up data, and handling updates according to the conditions that are currently in place. 

SUMMARY. 

Data Integrity Software enhance a concept that works toward ensuring that the accuracy, completeness, and consistency of data are maintained while making it valid.

By following the process, organizations make it paramount to have accurate and correct data in their database. The qualities that are focused upon include the data being attributable, legible, contemporary, original, and accurate. 

Data integrity tools, therefore, provide the umbrella that embraces all the aspects of security and quality that brings forth retention of relevant data while destroying irrelevant data.

There’s also the aspect of compliance with relevant industry and government regulations that data integrity deals with.

Author

Edward is a full-time blogger and affiliate marketing expert. Join Edward and other readers on webinfoed.com to learn how to scale your e-commerce business. Before this blog, Edward managed digital marketing teams for different companies and reviews best software that could help companies run their online business. Edward has been featured in more than 100 publication including vingle,designevo and business insider.

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