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What You'll Learn
Master Data Management
Forward-thinking organizations are driven by data. But what if that data is of bad quality? It is financially and operationally damaging for the organization. It’s important that you consider data quality as the foundation of compliance, advanced analytics, your AI initiatives, and customer trust. And to elevate data quality from reactive cleanses to proactive governance, we have put together some top data quality tools worth your serious evaluation in this blog.
Gartner defines data quality tools as the “processes and technologies for identifying, understanding and correcting flaws in data that support effective information governance across operational business processes and decision making.”
1. Informatica Data Quality
Informatica is recognized for its rich toolkit for data profiling, data cleansing, data matching, and data enrichment. This suite excels in both traditional and cloud-native environments. It provides users with AI-driven recommendations that simplify data quality rule creation across structured and semi-structured data. If you are an organization operating in a hybrid setup and seeking a proven, scalable solution – Informatica is the data quality tool for you.
One thing to watch for is a learning curve that requires dedicated adoption efforts. The configuration can seem complex. But fret not! LumenData can help. We are proud platinum enterprise partners with Informatica, and our technical consultants have achieved over 173 Informatica Certifications. Currently, we’re leading the single, largest Informatica MDM SaaS migration for a global cruise line. Our expertise in data migration from on-prem to Informatica SaaS MDM, coupled with customizable modernization accelerators, enables rapid deployment of Informatica solutions. Know more about our Informatica implementation services and success stories here
2. Oracle Enterprise Data Quality
The best part here is that the tool is deeply integrated with the Oracle ecosystem. And the tool is extremely good at data profiling, data cleansing, and data matching, especially for enterprise-grade master data. We recommend organizations already heavily invested in Oracle technologies opt for Oracle Enterprise Data Quality.
The tool has a premium pricing model and may offer limited flexibility outside Oracle environments. LumenData can help you if you choose to work on Oracle Enterprise Data Quality. We are proud gold partners with Oracle and have many success stories with them. One of the stories is about a Renowned Global Nutrition Company. They were struggling with an extremely rigid data infrastructure leading to poor customer experience across touchpoints like stores, e-commerce, and call centers. We consolidated around 25MM client records for them. We cleansed and standardized products across 5 categories and 100 sub-categories. One of the impactful outcomes was the conversion of 100K products and 70 attribute groups. Access the case study here.
3. Collibra Data Quality & Observability
The tool is a good combination of data governance, data lineage, and data quality dashboards. Collibra will provide you with strong issue workflows, metrics, and stakeholder visibility. It is best fit for organizations that are governed by compliance and need auditability and enterprise control. It’s easier to simplify data quality rule creation with Collibra as it provides auto-generated rules that are automatically linked to your data. You also get automated data quality monitoring and data quality assessment with Collibra.
However, it’s important to note that Collibra focuses heavily on governance. You may require complementary tools for deep data cleansing. LumenData is a technology partner with Collibra and can help you with your Collibra setup.
4. Ataccama ONE
This tool is ideal for enterprises that are seeking unified data governance, data quality, and data management. Ataccama ONE delivers an end-to-end platform. You get built-in AI that helps automate data profiling, anomaly detection, and data rule creation. Now this is ideal for large-scale pipelines. Ataccama ONE is a good option for regulated industries that require to manage data quality and data governance in real-time.
But one thing to note is that the platform has complex set-up and licensing. It will require specialist training.
5. IBM InfoSphere QualityStage
The tool is designed for heavy-duty enterprise needs and was named a Leader in the 2024 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions.
QualityStage provides you with deep cleansing, entity resolution, and real-time data validation.
In our view, IBM-environment organizations that require high throughput and compliance can opt for QualityStage. We say this because the tool is geared toward IBM-centric tech stacks. This may limit flexibility elsewhere.
6. Open-Source tools like Great Expectations & Apache Griffin
These tools are ideal for engineering-led teams that are embracing modern data stacks.
Great Expectations enables data quality rules and automated testing within data pipelines. It is extensible via Python SQL. Apache Griffin is designed for batch and streaming environments. It offers scalable data profiling, data validation, and data monitoring in big data ecosystems. But one thing to note regarding these tools is that they require technical expertise and ongoing maintenance to scale. If you are ready for it, then they can work wonders for you.
The LumenData team has put together an interesting data sheet on the prerequisites for mastering data quality on the Databricks platform using the Great Expectations library. Read it here.
Wrapping Up
Remember investing in data quality initiatives or data quality tools shouldn’t be a one-time thing. You need to leverage data quality as a continuous capability. When you have the right set of data quality tools and strategic investment, your enterprise can use data as a true asset. Remember, it is not necessary that one data quality tool solves everything. You may be required to combine data cleansing or data governance tools with data monitoring tools.
One last thing that we want to emphasize is that pilot before scaling. It’s a strategic step to test the tool you select. Test with key datasets to measure ease-of-use, performance, and team adoption.
We recommend identifying core use cases first and then match tools accordingly. LumenData is a premier provider of data quality services and consulting in the U.S. We can help you with this. Our solution experts have multiple years of experience in working with leading tools like Informatica, Oracle, and many others. They can design the most appropriate governance frameworks for your business. Connect with us today.
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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