The Top 20 Data Catalogs On The Market [2024]
Introduction
An essential competitive battleground of our time is data. Organizations have started to discover that they have vast amounts of data and that these can be real assets that can be used for analysis and decision-making. Data Catalogs play a huge role and are becoming an essential part of modern data management.
Data Catalogs revolve around a simple idea- It should be easy to find what you want even when many options exist. When you have many data sets, you must have a Data Catalog in some form or another;
Users with a curated portfolio of internal and external data will obtain even more business value from their data and analytics efforts because Data Catalogs can make it available and visible.
We've seen many organizations, from banks, pharmaceuticals, and law firms make drastic and multimillion-dollar adjustments to their operations due to what they found through data.
What is Data Catalog?
A Data Catalog is a set of metadata (descriptive data about the data itself) along with data management and search functions that aid analysts and other data users in discovering the data they need, providing an inventory of available data, and information allowing users to assess the fitness of specific data sets for intended uses.
Data administration, searching, data inventory, and data evaluation are all included in this brief definition, and they all depend on the fundamental capability to provide a metadata collection.
Data Catalogs have become the benchmark for metadata management in the era of big data and self-service business analytics. Today's metadata requirements are more extensive than those of the BI era; for one, Data Privacy is now a big constraint people need to deal with.
Why Do We Need Data Catalogs?
The difficulties of data management have intensified over the past several years. Organizations can't ignore the complexity of big data, cloud hosting, self-service analytics, and tightening regulations. Data Management is a top priority for organizations; however, it is difficult. Data Catalogs play a key role in addressing these obstacles.
Some smart people understood the opportunity and created Data Catalogs to assist data analysts in locating and analyzing data. Before Data Catalogs, most data analysts operated in the dark, without access to data sets, the description of their contents, their quality, and usefulness. We created Data Catalogs to solve these problems.
The Data Catalog has increased in capability, popularity, and importance since its modest beginning as a way to manage data inventories and expose data sets to analysts. Modern Data Catalogs continue to meet the needs of data analysts, but they have expanded their range. They're now at the foundation of data stewardship, curation, collaboration, and data governance adoption. As a result, Data Catalogs have become essential in organizations’ Data Strategies.
The different types of Data Catalogs
In recent years, the choices of Data Catalog tools have grown massively. Data Catalogs are broadly divided into these categories :
Standalone - includes data sets and operations catalog, supports data set evaluation, and a high level of integrations (often custom!) is required for a seamless user experience. An example: Alation
Integrated with Data Preparation - tools with broad data preparation capabilities and functionalities often tack on a catalog to inventory data sets and carry out specific actions. An example: Alteryx
Integrated with Data Analysis - tools with rich data analysis and visualization capabilities and functionalities that have extended their “report portals” to include data cataloging. The same challenges exist for the standalone type. An example: Tableau
Fully Integrated Solution- A tool with broad features and functionalities for data preparation, analysis, visualization, governance, master data management, data quality, and/or security almost always includes cataloging. When several data preparation and analysis technologies are utilized in an organization, interoperability becomes essential. An example: Ataccama
The value of a consistent user experience throughout the analytics lifecycle is clear; Data Catalog evolution is moving toward convergence. Most tools will evolve into fully integrated systems that handle all three capabilities—cataloging, preparation, and analysis. Conversely, convergence does not negate the requirement for compatibility, as self-service analysts frequently choose to select their preparation and analysis tools.
How should we evaluate Data Catalog?
Alert readers looking for a Data Catalog range from business and data analysts to C-level executives. The choice of a Data Catalog impacts day-to-day tactical activities and long-term strategic objectives.
Finding a top Data Catalog that satisfies your needs, caters to your interests, and suits your environment and culture is significant work. With such a wide range of users, data, use cases, and technical skills, it gets complicated too. An intuitive user interface and ease of usage are required to achieve universal Data Catalog acceptance, but that’s just the start.
Our experience has made us include the following criteria every time we help clients choose a new Data Catalog / Metadata Management solution. The twenty features or functions given below are intended to guide you through the evaluation process and help you choose the best data catalog in 2024 that is most suited for your organization, but this is not an exhaustive list:
Cataloging Data Sets
Cataloging Data Operations
Searching
Recommendations
Data Set Evaluation
Data Access
Usage Metadata
Data Valuation
Metadata Catalog
Security
Lineage
Compliance
Quality
Data Curation
Socialization
Integration and Interoperability
Deployment
Services
Pricing
Vendor Roadmap
Top Metadata Management Tools
A Data Catalog's core is metadata. Every Data Catalog collects information about the data inventory as well as data-related processes, people, and platforms. Data Catalog tools serve considerably broad purposes and use cases. They contain metadata for and about people, as well as metadata for and about datasets, processing, searches, and usage!
Metadata concerns key aspects of recorded data, such as data type, storage location, size, version, and hardware or software connectivity. It also includes names of stewards and data owners, when the data was last accessed, how often, and even which other data sets are used alongside a particular one. Metadata makes data easier to find and retrieve, faster to recognize, and more efficient to use for specified purposes.
Below is a list of metadata management tools (a.k.a. Data Catalogs, or at least including that functionality). Incept Data Solutions is a technology implementation partner with all those in yellow. It is by no means exhaustive. We threw an extra one in, for a total of 21:
Informatica EDC (with AXON); CDGC- Technical data, such as database schemas, mappings, and code, business data (glossary terminology, governance processes), operational and infrastructure data (run-time stats and time stamps), and consumption data are all accessible through Informatica Metadata Management (user ratings and comments). By combining AI and machine learning, Informatica develops a knowledge graph of an organization's data assets and relationships. Informatica's Intelligent Data Platform is built on the foundation of active metadata.
Collibra-Collibra is a Data Intelligence organization that connects the correct data, insights, and algorithms to Data Citizens to expedite trusted business outcomes. The cloud-based platform integrates IT and the business to help the digital enterprise develop a data-driven culture.
Alation- According to Alation, customers use the Data Catalog as a platform to drive data search and discovery, data governance, data stewardship, analytics, and cloud transition. Thanks to its behavioral and linguistic intelligence technologies, collaboration capabilities, and open interfaces, Alation provides a platform for a wide range of metadata management applications by combining machine learning with human insight to tackle the most challenging challenges in data management.
Ataccama- One of the exciting new entries here, they describe themselves as a unified platform for automated data quality, MDM, and metadata management—Ataccama ONE specializes in complex enterprise data governance solutions that provide sustainable, long-term value. It is more of a Data Quality solution to be sure, but it is one of those that is aiming to be fully integrated.
Data.World- It calls itself the enterprise data catalog for the modern data stack. Their cloud-native SaaS platform leverages the power of the knowledge graph to make data discovery, governance, and analysis easy, turning data workers into knowledge superheroes.
Microsoft's Azure Data Catalog- Microsoft's Azure Data Catalog is an enterprise-wide metadata catalog meant to simplify data asset discovery and a fully-managed service that allows analysts to search for data assets. Registering, enriching, discovering, understanding, and consuming data sources is a task for data scientists and developers.
Oracle Enterprise Metadata Management ( OEMM)- Oracle Enterprise Metadata Management (OEMM) is a platform for managing metadata. OEMM can collect and Catalog information from various sources, including relational databases, Hadoop, ETL, BI, data modeling, and more. Additionally, OEMM enables interactive searching.
SAP Information Steward- SAP Information Steward software allows you to monitor, evaluate, and improve data integrity. Combine data profiling with metadata management solutions to gain continuous insight into the quality of company data, improve operational, analytical, and data governance, and optimize operations.
IBM Watson Knowledge Catalog- IBM Watson Knowledge Organize is a cloud-based enterprise metadata repository allowing customers to catalog knowledge and analytics assets, such as machine learning models and structured and unstructured data, making them easily accessible and useable.
Atlan-Atlan is a data collaboration platform. Atlan enables teams to create a single source of truth for all their data assets by acting as a virtual hub for data assets ranging from tables and dashboards to models and code, and collaborate across the modern data stack through deep integrations with tools like Slack, BI tools, data science tools, and more. Search, Cataloging, and browsing data assets are all essential features (tables, BI dashboards, etc.). They are creating a profile for data assets - automatic data quality profiling, wikis, etc. Enable collaboration – link sharing, chat plugins, BI tool connectors, and so on. Data governance — auto-PII, granular access restriction, column-level lineage creation, and so on.
ASG Data Intelligence- It assists enterprises in successfully implementing defensive and offensive data strategies by recording and managing information supply chains that enable stakeholders to access, understand, exchange, and analyze trusted data. ASG can ingest and understand metadata from various sources, including relational databases, data warehouses, big data, ETL tools, source code, business intelligence tools, enterprise applications, and file systems.
Alex Solution- Alex Solutions provides a corporate Data Catalog with a business lexicon that allows users to develop and preserve business words while connecting them to actual data assets, processes, and output. It also provides policy-driven data quality, including data lineage, profiling, and intelligent tagging based on machine learning.
Erwin Data Intelligence-Erwin Data Intelligence combines Data Catalog and Data Literacy to increase knowledge of and access to accessible data assets, as well as guidance on how to use them and safeguards to ensure data policies and best practices are followed. The service helps customers locate, harvest, arrange and deploy data sources by connecting physical metadata to specific business words and meanings. Erwin can ingest metadata from data integration tools and cloud-based platforms and evaluate intricate relationships between systems and use cases.
Talend Data Integrity and Governance- Talend helps you fight data chaos with a unified platform to discover, federate, and share trusted data to all the people who need it, so they can spend their time on revenue-generating tasks. Because data is useless until it’s clean, compliant, and accessible, data integrity and governance are essential capabilities of the Talend Data Fabric platform.
Precisely-Data Cataloging, Business Glossaries data lineage, and metadata management are among the integrated data governance features offered by Infogix. Customizable dashboards and zero-code procedures are also included. Reference customers use Infogix for data governance, risk, compliance, and value management. The device is adaptable and can handle smaller data analysis projects.
Manta- technically not a Data Catalog, but it does have cataloging features. MANTA is a uniform data lineage platform that maps all data flows and gives you a complete picture of your data. The tool shows you where the data comes from and travels via all data processing systems. MANTA updates lineage automatically as needed and displays data flows in a user-friendly, clear, and intelligible manner. The solution was also created to fit into any data management environment.
Qlik Catalog & Lineage- Qlik states that their catalog and lineage capabilities help you fully understand the data flowing through your analytics data pipelines – from source to use. Confidently broaden access and usage of your analytics. Build trust in your data and insights. Accelerate migration to modern analytics in the cloud.
Octopai- Octopai is a cross-platform metadata management automation solution for data and analytics teams that allows them to identify and regulate shared metadata. The product gathers metadata from ETL, databases, and reporting systems to perform metadata scanning. Metadata is centralized and handled, and an intelligent engine with hundreds of crawlers searches and provides results quickly. Octopai is excellent for business intelligence, governance, and Data Cataloging use cases.
Poolparty- it calls itself a “semantic suite”. PoolParty Semantic Suite provides the necessary tools and algorithms to transform your existing data and content into powerful knowledge systems by combining artificial and human intelligence. With features like Semantic Search Recommender Systems, Question Answering Systems, Concept Tagging, and Metadata Management & Data Governance, it promises a lot indeed.
OvalEdge- OvalEdge is an on-premises Data Catalog and governance solution that crawls databases, data lakes, and back-end systems to produce an intelligent Catalog of data. The product is a data discovery tool that rookie and professional analysts can use to find data rapidly. Built-in governance tools in OvalEdge assist build a standard business vocabulary, data assets, PII, and access restrictions for distinct roles. It also uses machine learning and powerful algorithms to organize data automatically.
Smartlogic Semaphore- Semaphore is a semantic platform that enables businesses to enrich data, extract facts, and unify data sources. The solution uses a rule-based, model-driven approach to improve the capabilities of existing technology. Users can utilize Smartlogic to drive self-service delivery and change enterprise search from keyword to semantic to identify data connected to a query. Smartlogic is well-known for its modeling, metadata transformation, and generation tools.
There are others, to be sure, but ultimately organizations focus on the Gartner leaders unless their use case is very specific.
Data insights can be accessed, located, shared, and operationalized faster in organizations with a strong metadata management culture. Data culture plays an important role, however. A certain Data Catalog may seem great to IT folks, but if business users don’t use it, what’s the point?
What is an Enterprise Data Catalog?
An enterprise data catalog is like a data treasure map for companies, guiding them to easily find and understand their data. It's a one-stop-shop for organizing and managing all data assets, ensuring everything from data quality to security is top-notch.
If you're wondering when to buy a data catalog tool or how to buy a data catalog, the answer lies in recognizing the right time and approach for your enterprise. An enterprise data catalog is essential when data becomes too vast to handle manually and you need a reliable system to maintain data quality and compliance. When ready to invest, look for a tool that's a perfect fit for your company's size, needs, and data strategy.
What happens when we don't have a Data Catalog?
Without a Data Catalog, data professionals will look for data by searching through documents, consulting with coworkers, relying on tribal knowledge, or simply working with datasets they are familiar with (some extract loaded into Excel, anyone?). Trial and error, inefficiency and a lot of rework, and repeated dataset discovery (reinventing the wheel) are all part of the process, which frequently leads to working with "close enough" data when time is running out.
With a Data Catalog, an analyst can swiftly search for and identify data, see all accessible datasets, evaluate and make informed decisions about which data to use, and do data preparation and analysis efficiently and confidently. It's usual to switch from spending 80% of their time finding data and just 20% of their time analyzing, reversing those metrics completely.
The quality of the analysis is significantly improved, and the organization's research capacity has increased without adding new analysts. Data Catalogs lead to improved data trust.
Closing
It's challenging to manage data in the age of big data, data lakes, and self-service: data is everywhere! The ability to find reports, data, and people who can explain edge cases and validate your work is needed to become a data-driven organization. Active data curation is an essential strategy for modern data management and a Data Catalog is where these “intelligent” data sets (prepared) should be published.
Data Catalogs help in addressing those challenges.
