Atlan Earns Forrester’s Top Rating by Reimagining the Data Control Plane

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Key Takeaways:

– Atlan takes top spot in Forrester’s Enterprise Data Catalog rating, outpacing established players.
– Atlan’s data catalog uses AI and machine learning to aid in metadata tracking, reducing manual burden.
– Atlan uses a graph database to enhance metadata tracking for strong customer access and visibility.
– The company is set for more innovations and aims to become the control plane for data and AI.

Atlan’s Enterprise Data Catalog Wins Forrester’s Praise

Startup Atlan has scored big, bagging the top rating from Forrester in their wave for enterprise data catalogs. The company earned a score of 4.20 for its enterprise data catalog and a 4.50 for its strategy, the highest among all twelve competitors evaluated in the study. Atlan CEO Prukalpa Shankar promises more innovation in the data catalog sector.

Albeit a younger entrant in the market, Atlan’s progress is swift and consistent. Its failure to secure the first place for market presence doesn’t overshadow its potential and momentum. The six-year-old company scored 2.00, trailing behind older, larger, and more established players.

The Heart of Atlan’s Success: Automation and AI

Atlan’s success lies in its meticulously crafted strategy that anticipates and addresses strategic customer needs through automation. Forrester lead analyst Jayesh Chaurasia applauds Atlan as a visionary player with the ambition to become the data and AI control plane enabling complex business use cases.

Forrester analysts favored many aspects of Atlan’s offering, including its unique ability to enable data democratization and self-service through automated metadata tracking. They also appreciated its use of GenAI to assist with discovery, its end-to-end lineage tracking, and creating a Netflix-like personalized experience for all business and technical personas. These factors significantly contributed to Atlan outshining its peers.

While Atlan scored low in revenue due to its relative newness in the field, it earned favorable scores for its growing customer base, indicating promising growth.

Three Types of Data Catalogs: Atlan’s Perspective

Prukalpa Shankar, Atlan CEO and co-founder, differentiates data catalogs into three types. The first is the technical metadata catalog that allows data sharing, like Amazon Glue. The second type is the data dictionary version which requires a good user experience. It includes products like Tableau’s Data Catalog and dbt Labs Explorer.

The third type, representing Atlan’s vision, is the control plane version of a data catalog. It is an intelligent system that brings together metadata from various ecosystems to drive use cases across these ecosystems.

Atlan’s Control Plane: Embracing Diversity and automation

The control plane version that Atlan builds accommodates a large range of data, users, and tools. It thrives on the diversity, whether it’s data types, user roles ranging from data analysts to data scientists, or a plethora of tools ranging from BI products to ETL, and data warehouses to date lakes.

Atlan has effectively leveraged AI and machine learning to automate metadata tracking. This automation reduces the burden of manual data management, allowing data stewards to focus more on strategizing and decision-making. Shankar further explains the significance of automated metadata tracking in the future, with the ever-increasing variety and volume of use cases.

Towards an Open Standards World

Shankar is hopeful about a future with more open standards. She envisions a shift towards open standards from the data lake layer. While Atlan’s product may not be open source, it aims to remain open with its platform and access to metadata.

The Journey Forward

While the data management challenges remain consistent, the parameters defining these challenges have evolved. Today, the data types, places for consumption, and timelines have changed drastically. Navigating these transformations, Atlan continues to reimagine data control planes, staying committed to eliminating data confusion and promoting data-driven decision making for its customers.

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