#querysurge

[satvikasailu6]

Leading Tableau Test Automation Tools — Comparison and Market Leadership

Automated testing for Tableau dashboards and analytics content is a growing niche, with a few specialized commercial tools vying for leadership. 

We compare the top solutions — Datagaps BI Validator, Wiiisdom Ops (formerly Kinesis CI), QuerySurge, and others — based on their marketing presence, enterprise adoption, feature set (especially for functional/regression testing), CI/CD integration, and industry reputation. 

Datagaps BI Validator (DataOps Suite)

Industry sources describe BI Validator as a “leading no-code BI testing tool” . It has recognition on review platforms; for example, G2 reviewers give the overall Datagaps suite a solid rating (around 4.0–4.6/5) and specifically praise the Tableau-focused module

Industry sources describe BI Validator as a “leading no-code BI testing tool” . It has recognition on review platforms; for example, G2 reviewers give the overall Datagaps suite a solid rating (around 4.0–4.6/5) and specifically praise the Tableau-focused module.

Customer Adoption: BI Validator appears to have broad enterprise adoption. Featured customers include Autotrader, Portland General Electric, and University of California, Davis. 

A case study mentions a “Pharma Giant” cutting Tableau upgrade testing time by 55% using BI Validator.

Users on forums often recommend Datagaps; one BI professional who evaluated both Datagaps and Kinesis-CI reported that Datagaps was “more capable” and ultimately their choice . Such feedback indicates a strong reputation for reliability in complex enterprise scenarios.

Feature Set: BI Validator offers end-to-end testing for Tableau covering:

Functional regression testing: It can automatically compare workbook data, visuals, and metadata between versions or environments (e.g. before vs. after a Tableau upgrade) . A user notes it enabled automated regression testing of newly developed Tableau content as well as verifying dashboard outputs during database migrations . It tests dashboards, reports, filters, parameters, even PDF exports for changes.

Data validation: It can retrieve data from Tableau reports and validate against databases. One review specifically highlights using BI Validator to check Tableau report data against the source DB efficiently . The tool supports virtually any data source (“you name the datasource, Datagaps has support for it”

UI and layout testing: The platform can compare UI elements and catalog/metadata across environments to catch broken visuals or missing fields post-migration.

Performance testing: Uniquely, BI Validator can simulate concurrent user loads on Tableau Server to test performance and robustness . This allows stress testing of dashboards under multi-user scenarios, complementing functional tests. (This is analogous to Tableau’s TabJolt, but integrated into one suite.) Users have utilized its performance/stress testing feature to benchmark Tableau with different databases.

Datagaps provides a well-rounded test suite (data accuracy, regression, UI regression, performance) tailored for BI platforms. It is designed to be easy to use (no coding; clean UI) — as one enterprise user noted, the client/server toolset is straightforward to install and navigate.

CI/CD Integration: BI Validator is built with DataOps in mind and integrates with CI/CD pipelines. It offers a command-line interface (CLI) and has documented integration with Jenkins and GitLab CI, enabling automated test execution as part of release pipelines . Test plans can be scheduled and triggered automatically, with email notifications on results . This allows teams to include Tableau report validation in continuous integration flows (for example, running a battery of regression tests whenever a data source or workbook is updated). The ability to run via CLI means it can work with any CI orchestrator (Jenkins, Azure DevOps, etc.), and users have leveraged this to incorporate automated Tableau testing in their DevOps processes.

Wiiisdom Ops (formerly Kinesis CI)

Wiiisdom (known for its 360Suite in the SAP BusinessObjects world) has since rebranded Kinesis CI as Wiiisdom Ops for Tableau and heavily markets it as a cornerstone of “AnalyticsOps” (bringing DevOps practices to analytics). 

The product is positioned as a solution to help enterprises “trust their Tableau dashboards” by automating testing and certification . Wiiisdom has been active in promoting this tool via webinars, Tableau Conference sessions, e-books, and case studies — indicating a growing marketing presence especially in the Tableau user community. Wiiisdom Ops/Kinesis has a solid (if more niche) reputation. It’s Tableau-exclusive focus is often viewed as strength in depth. 

The acquiring company’s CEO noted that Kinesis-CI was a “best-in-breed” technology and a “game-changer” in how it applied CI/CD concepts to BI testing . While not as widely reviewed on generic software sites, its reputation is bolstered by public success stories: for instance, Red Hat implemented Wiiisdom Ops for Tableau and managed to reduce their dashboard testing time “from days to minutes,” while handling thousands of workbooks and data sources . Such testimonials from large enterprises (Red Hat, and also Gustave Roussy Institute in healthcare ) enhance Wiiisdom Ops’ credibility in the industry. 

Customer Adoption: Wiiisdom Ops is used by Tableau-centric organizations that require rigorous testing. The Red Hat case study is a flagship example, showing adoption at scale (5,000+ Tableau workbooks) . Other known users include certain financial institutions and healthcare organizations (some case studies are mentioned on Wiiisdom’s site). Given Wiiisdom’s long history with BI governance, many of its existing customers (in the Fortune 500, especially those using Tableau alongside other BI tools) are likely evaluating or adopting Wiiisdom Ops as they extend governance to Tableau. 

While overall market share is hard to gauge, the tool is gaining traction specifically among Tableau enterprise customers who need automated testing integrated with their development lifecycle. The acquisition by Wiiisdom also lends it a broader sales network and support infrastructure, likely increasing its adoption since 2021. 

Feature Set: Wiiisdom Ops (Kinesis CI) provides a comprehensive test framework for Tableau with a focus on functional, regression, and performance testing of Tableau content.

QuerySurge (BI Tester for Tableau)

Marketing & Reputation: QuerySurge is a well-known data testing automation platform, primarily used for ETL and data warehouse testing. While not Tableau-specific, it offers a module called BI Tester that connects to BI tools (including Tableau) to validate the data in reports. QuerySurge is widely used in the data quality and ETL testing space (with many Fortune 500 users) and is often mentioned as a top solution for data/ETL testing. 

Its marketing emphasizes ensuring data accuracy in the “last mile” of BI. However, QuerySurge’s brand is stronger in the data engineering community than specifically in Tableau circles, since it does not perform UI or functional testing of dashboards (it focuses on data correctness beneath the BI layer). 

Customer Adoption: QuerySurge has a broad user base across industries for data testing, and some of those users leverage it for Tableau report validation. It’s known that organizations using multiple BI tools (Tableau, Cognos, Power BI, etc.) might use QuerySurge centrally to validate that data shown in reports matches the data in the warehouse. The vendor mentions “dozens of teams” using its BI integrations to visualize test results in tools like Tableau and Power BI , suggesting an ecosystem where QuerySurge ensures data quality and BI tools consume those results. 

Notable QuerySurge clients include large financial institutions, insurance companies, and tech firms (as per their case studies), though specific Tableau-centric references are not heavily publicized. As a generic tool, its adoption overlaps with but is not exclusive to Tableau projects

Feature Set: For Tableau testing, QuerySurge’s BI Tester provides a distinct but important capability: datalevel regression testing for Tableau reports. Key features include.

Conclusion: 

The Market Leader in Tableau Testing Considering the above, Datagaps BI Validator currently stands out as the best all-around commercial Tableau testing tool leading the market. It edges out others in terms of breadth of features and proven adoption. 

Enterprises appreciate its ability to handle everything from data validation to UI regression and performance testing in one package . 

Its multi-BI versatility also means a wider user base and community knowledge pool. Many practitioners point to BI Validator as the most “efficient testing tool for Tableau” in practice . That said, the “best” choice can depend on an organization’s specific needs. Wiiisdom Ops (Kinesis) is a very close competitor, especially for organizations focusing solely on Tableau and wanting seamless CI/CD pipeline integration and governance extras. 

Wiiisdom Ops has a strong future outlook given its Tableaufocused innovation and success stories like Red Hat (testing time cut from days to minutes) . It might be considered the leader in the Tableau-only segment, and it’s rapidly gaining recognition as Tableau customers pursue DevOps for analytics. 

QuerySurge, while not a one-stop solution for Tableau, is the leader for data quality assurance in BI and remains indispensable for teams that prioritize data correctness in reports . It often complements either Datagaps or Wiiisdom by covering the data validation aspect more deeply. In terms of marketing presence and industry buzz, Datagaps and Wiiisdom are both very active: 

Datagaps publishes thought leadership on BI testing and touts AI-driven DataOps, whereas Wiiisdom evangelizes AnalyticsOps and often partners with Tableau ecosystem events. Industry analysts have started to note the importance of such tools as BI environments mature. 

In conclusion, Datagaps BI Validator is arguably the market leader in Tableau test automation today — with the strongest combination of features, enterprise adoption, and cross-platform support . Wiiisdom Ops (Kinesis CI) is a close runner-up, leading on Tableau-centric continuous testing and rapidly improving its footprint . Organizations with heavy data pipeline testing needs also recognize QuerySurge as an invaluable tool for ensuring Tableau outputs are trustworthy . 

All these tools contribute to higher confidence in Tableau dashboards by catching errors and regressions early. As analytics continues to be mission-critical, adopting one of these leading solutions is becoming a best practice for enterprises to safeguard BI quality and enable faster, error-free Tableau deployments

[gqattech]

ETL and Data Testing Services: Why Data Quality Is the Backbone of Business Success | GQAT Tech

Data drives decision-making in the digital age. Businesses use data to build strategies, attain insights, and measure performance to plan for growth opportunities. However, data-driven decision-making only exists when the data is clean, complete, accurate, and trustworthy. This is where ETL and Data Testing Services are useful.

GQAT Tech provides ETL (Extract, Transform, Load) and Data Testing Services so your data pipelines can run smoothly. Whether you are migrating legacy data, developing on a data warehouse, or merging with other data, GQAT Tech services help ensure your data is an asset and not a liability.

What is ETL and Why Is It Important?

ETL (extract, transform, load) is a process for data warehousing and data integration, which consists of: 

Extracting data from different sources

Transforming the data to the right format or structure

Loading the transformed data into a central system, such as a data warehouse. 

Although ETL can simplify data processing, it can also create risks in that data can be lost, misformatted, corrupted, or misapplied transformation rules. This is why ETL testing is very important. 

The purpose of ETL testing is to ensure that the data is:

Correctly extracted from the source systems

Accurately transformed according to business logic

Correctly loaded into the destination systems.

Why Choose GQAT Tech for ETL and Data Testing?

At GQAT Tech combine our exceptional technical expertise and premier technology and custom-built frameworks to ensure your data is accurate and certified with correctness.

1.  End-to-End Data Validation

We will validate your data across the entire ETL process – extract, transform, and load- to confirm the source and target systems are 100% consistent.

2. Custom-Built Testing Frameworks

Every company has a custom data workflow.  We build testing frameworks fit for your proprietary data environments, business rules, and compliance requirements.

3. Automation + Accuracy

We automate to the highest extent using tools like QuerySurge, Talend, Informatica, SQL scripts, etc. This helps a) reduce the amount of testing effort, b) avoid human error.

4. Compliance Testing

Data Privacy and compliance are obligatory today.  We help you comply with regulations like GDPR, HIPAA, SOX, etc.

5. Industry Knowledge

GQAT has years of experience with clients in Finance, Healthcare, Telecom, eCommerce, and Retail, which we apply to every data testing assignment.

Types of ETL and Data Testing Services We Offer

Data Transformation Testing

We ensure your business rules are implemented accurately as part of the transformation process. Don't risk incorrect aggregations, mislabels, or logical errors in your final reports.

Data Migration Testing

We ensure that, regardless of moving to the cloud or the legacy to modern migration, all the data is transitioned completely, accurately, and securely.

BI Report Testing

We validate that both dashboards and business reports reflect the correct numbers by comparing visual data to actual backend data.

Metadata Testing

We validate schema, column names, formats, data types, and other metadata to ensure compatibility of source and target systems.

Key Benefits of GQAT Tech’s ETL Testing Services

1. Increase Data Security and Accuracy

We guarantee that valid and necessary data will only be transmitted to your system; we can reduce data leakage and security exposures.

2. Better Business Intelligence

Good data means quality outputs; dashboards and business intelligence you can trust, allowing you to make real-time choices with certainty.

3. Reduction of Time and Cost

We also lessen the impact of manual mistakes, compress timelines, and assist in lower rework costs by automating data testing.

4. Better Customer Satisfaction

Good data to make decisions off of leads to good customer experiences, better insights, and improved services.

5. Regulatory Compliance

By implementing structured testing, you can ensure compliance with data privacy laws and standards in order to avoid fines, penalties, and audits.

Why GQAT Tech?

With more than a decade of experience, we are passionate about delivering world-class ETL & Data Testing Services. Our purpose is to help you operate from clean, reliable data to exercise and action with confidence to allow you to scale, innovate, and compete more effectively.

Visit Us: https://gqattech.com Contact Us: info@gqattech.com

[pythonjobsupport]

How to Build a DevOps for Data Testing Pipeline from Jenkins to JIRA

This was the 3th webinar in a 4-part series on data validation & ETL testing with QuerySurge. And each webinar is only 30 … source

[devopssolutions]

Most important DevOps tools you should know 2021

DevOps refers to a methodology, which integrates software development and IT operations. It provides the optimum choice to the business enterprise in launching the new software, thereby making quick changes to the potential audience in no time through the use of automation.

Owing to the faster DevOps practices adoption, the DevOps tools are gaining high popularity over the past few years. There are a bunch of DevOps software tools that play an integral role in masking collaboration, transparency, and automation the focal point of the value stream.

Such tools promote a plethora of methodologies to exchange and share technical knowledge and data among a plethora of stakeholders efficiently. In this article, you can seek information about the most crucial DevOps tools and it will helpful to choose right devops service provider

QuerySurge

It is regarded as the smart data testing solution, which accomplishes the complete DevOps solution, to ensure consistent data testing. It facilitates seamless integration within the DevOps pipeline, thereby assuring continuous testing.

Moreover, it is useful in verifying massive data amounts faster. This tool is useful in validating the challenging transformation rules between the target systems and multiple sources. Other than this, it plays an integral role in diagnosing the code changes and needs, updation of the tests accordingly. Moreover, it provides notification to the team members of specific changes. Also, it offers detailed data analytics and data intelligence.

Docker

It has gained high prominence as a lighter DevOps tool, which is beneficial in boosting and easing various workflows within the SDLC through the combined methodology. The Docker container image comprises standalone and applicable images, which comprise what is necessary to execute the specific application.

Through Docker Engine, it is possible to seek access to the containers which helps in running the applications within the remote environment. This tool offers a helping hand in packing, executing, and handling a plethora of deployed apps. It allows you to explore a plethora of images from the authentic community and publishers.

Apart from this, it is useful to the developers in collaborating, testing, and creating. It comes with container runtime, which will be executed on the Linux Server Operating Systems and Windows. Also, it includes a standardized packaging format for a variety of applications.

Selenium

It is another popular DevOps tool, which helps to automate a plethora of web-based apps. In addition, it is effective in automating the administrative tasks and automation testing of web-based apps. It is possible to develop scalable scripts by using this tool. It helps to create a variety of testing scripts in different languages.

SonarQube

It is recognized to be an open-source DevOps tool, which offers support to more than 27 programming languages. It happens to be an excellent option to analyze the application's source code which is written in a plethora of languages.

This tool monitors the code base against a bunch of static code analysis rules. Hence, you will be successful in focusing on code security and code quality, during the software development process.

The Quality Gates are the other worth mentioning feature of this tool. It is useful in scoring the source code for the code smells, vulnerabilities, bugs, errors, duplications, coverage, to name a few. Hence, it is useful in assessing if it will pass the specific quality gate for the launch. In addition, it allows you to use the quality gates for the analysis of the pull requests, which helps in deciding whether you need to merge them or not.

Another reason why this tool has become the number one choice of the developers is that it helps in highlighting a plethora of newly introduced problems. Moreover, it offers a plethora of useful visualizations, which offers insight into the code base's entire state.

It works wonders on the premises and in the cloud. With the introduction of continuous code inspection within the DevOps workflow, this tool is useful in improving security.

Puppet

It is another popular DevOps tool, which handles, monitors so that you can keep up with the infrastructure faster. It is recognized to be a successful and well-renowned cross-platform configuration management tool, which plays an integral role in making the development process faster and secure.

Apart from this, this DevOps tool helps handle a plethora of servers. This tool offers a helping hand in handling a bunch of teams and resources. Furthermore, it is effective in managing a plethora of problems faster. It comprises various modules, which are combined with different DevOps tools.

With the treating of the entire infrastructure as a code, this tool plays an integral role in automating infrastructure management. It offers support to different operating systems like Windows, Linux, Unix, and various platforms, such as Cisco switches, macOS servers, and IBM mainframes.

Nagios

It is considered to be a well-renowned DevOps tool, which serves as the watchdog for the entire infrastructure and the system. The IT infrastructure teams make the right use of this tool to rectify and provide the solutions to the infrastructure-related problems before putting the specific team at the risk. In addition, it helps to check the protocols, apps, logs, network, database, to name a few.

This tool is useful in upgrading the infrastructure and maintenance schedules. It is also helpful in recognizing, assessing, and monitoring the crucial network infrastructure. Moreover, it is beneficial in checking the network traffic and available bandwidth to optimize the use. Also, it ensures simple log searching.

Git

It is another widely used and well renowned DevOps tool, which provides the optimum choice to the developers in monitoring the application development advancement with the maintenance of different source code versions. This tool provides limitless private repositories for about 5 team members. This tool enables a faster release cycle. In addition, it allows distributed development.

This DevOps tool is useful in automating the specific software development process. It provides the optimum choice to the software development team in automating a plethora of software development processes, such as dependency management, confliction management. Thus, it helps in decreasing a plethora of manual efforts.

[jennystevensstuff]

ETL Testing Service Market Size 2021 With Top Countries, Competitive Landscape, Industry Development and Revenue Analysis To 2027 by Value Market Research

The global ETL Testing Service Market report contains overall the details analysis based on few parameters like drivers, restraints, competitive analysis, latest trends and opportunities, geographical outlook, and competitive panel for the forecast timespan of 2021 to 2027. Therefore, these written statements reflect the overall market conditions and various other factors that are associated with the market that will definitely guide concerned parties in making a strategic decision.

The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the etl testing service market include 99 Percentage, Guru99, QualiTest, Codoid, RTTS, Infosys, Outsource2india, Flatworld Solutions, Datagaps, QA Mentor, QuerySurge and Others. This section consists of a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.

Get more information on "Global ETL Testing Service Market Research Report" by requesting FREE Sample Copy at

https://www.valuemarketresearch.com/contact/etl-testing-service-market/download-sample

[msgates]

QuerySurge is Now Available in the Microsoft Azure Marketplace Click here for articles March 18, 2021 at 06:12PM

[nareshithyderabad-blog]

Most Popular DevOps Tools In 2020

In 2009 the term "DevOps" was initially coined by Patrick Debois. DevOps provides quality software by shortening the developmental life cycle of a system. DevOps is a mash-up of operations and system development, by using agile methods it has increased software velocity.

Goals Of DevOps:

1. The primary goal of DevOps is to improve the efficiency of processing and retrieval time to decrease the rate of failure.

2.shorten the time in between fixes

3. improve the frequency of deployment

Top DevOps Tools to be followed in 2020

1.Basis Technologies

2.QuerySurge

3.Buddy

4.Kamatera

5.Jenkins

6.TestRail

1.Basis Technologies:

This technology provides test automation and DevOps mainly for SAP delivers safer, faster and frequent SAP changes at low cost and helps in staying competitive.

Features:

1. One can easily break the shackles of the release of regular cycles.

2. For the N+N SAP environment, automated code is merged.

3.Easy regulatory compliance through the audit trail.

2.QuerySurge:

For automated and continuous data testing this Querysurge is the smart DevOps solution.

Features:

1. Basing on run results it can custom flow

2.from data connections create staging tables

3. A large amount of data can be verified quickly

3.Buddy:

To decrease the entry thresholds Buddy CI/CD smart tool is used. For deploying, testing and building software delivery pipelines are used.

Features:

1.parellelism and Configuration of YALM are supported.

2. All popular frameworks and languages are supported.

3. Basing on charge sheets ensures light and fast deployments.

4.Kamatera:

This is the best and main DevOps tool which helps in using applications like Jenkins, MongoDB, MySQL, PhpMyAdmin, etc.

Features:

1.comes with a free trial version of 30 days

2.available in 13 data centers in 4 continents

3.can be scalable across servers in seconds

5.Jenkins:

This is a tool for monitoring of execution of the repetition of speed. It helps in quickly finding the issues and integrates them.

Features:

1. For any project to test and build virtually 400 plugins are offered.

2. It is a java-based program which runs on OS like UNIX, Windows and MAC OS

3.easy to configure through the web interface and easy to setup.

6.TestRail

It is the best management software tool that can efficiently track, organize and manage testing efforts. Kamatera can be installed on your own server or on SaaS /Cloud - solutions.

Features:

1.with email notifications, milestones and to-do lists it works efficiently

2. On the Atlassian Market, Jira plug-in is freely available.

3.plans and runs manual and automated test cases.

[satvikasailu6]

Exploring the World of ETL Automation Testing Tools

Understanding ETL Automation Testing:

ETL processes involve extracting data from source systems, transforming it into a suitable format, and loading it into a target system. Automation testing for ETL aims to verify the accuracy, completeness, and performance of these processes, reducing the risk of data errors and ensuring data quality.

Significance of ETL Automation Testing:

Data Integrity: ETL automation testing tools help ensure that data is extracted, transformed, and loaded accurately, preventing discrepancies that could compromise data integrity.

Efficiency: Automated testing accelerates the testing process, allowing for more frequent and thorough validations, thereby improving the efficiency of ETL development cycles.

Error Detection: Automation tools are adept at detecting errors and anomalies in the data, allowing teams to identify and rectify issues promptly.

Popular ETL Automation Testing Tools:

1. Apache JMeter:

Apache JMeter, initially designed for load testing, has found utility in ETL testing. Its flexibility and ability to simulate user behavior make it suitable for assessing the performance and scalability of ETL processes.

2. QuerySurge:

QuerySurge is a dedicated ETL testing tool that streamlines data validation processes. With features like test case management and comprehensive reporting, QuerySurge ensures the reliability of data warehouses and ETL processes.

3. Talend Open Studio for Data Integration:

Talend, an open-source ETL tool, provides a comprehensive suite for data integration and transformation. It supports testing through built-in features for data quality and validation, making it a popular choice for ETL development.

4. Informatica Data Validation Option (DVO):

Informatica DVO is a specialized testing tool designed for ETL testing within the Informatica PowerCenter ecosystem. It automates the testing of data integration processes, ensuring the accuracy of data processing.

5. Apache Nifi:

While not specifically designed for testing, Apache Nifi is an open-source data integration tool that can be employed for monitoring and managing data flows. Its user-friendly interface makes it useful for verifying ETL processes.

Conclusion:

In conclusion, ETL automation testing is a critical aspect of maintaining data quality and integrity in today's data-driven world. The right choice of ETL automation testing tool depends on the specific needs of your organization, the complexity of your data integration processes, and your team's expertise.

As you explore the world of ETL automation testing tools, consider factors such as scalability, ease of use, and compatibility with your existing ETL infrastructure. Whether you opt for the flexibility of Apache JMeter, the dedicated features of QuerySurge, or the comprehensive suite of Talend, embracing automation testing is key to ensuring the seamless flow of high-quality data through your ETL pipelines.