Data analysis 2023-05-06
WatsonX.data by IBM icon

WatsonX.data by IBM

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Scaled analytics and data management for enterprises.
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Watsonx.data is a fit-for-purpose data store optimized for governed data and AI workloads, designed to help enterprises scale their analytics and AI capabilities.

With watsonx.data, users can quickly connect to data sources, get trusted insights and lower data warehouse costs. The tool is optimized for all data, analytics and AI workloads and features an open, hybrid and governed data store that allows users to access and share data.

Watsonx.data includes a shared metadata layer to access all data through a single point of entry, and built-in governance, security and automation to enhance trust in data.

The tool enables users to reduce the cost of their data warehouse by up to 50% by optimizing costly data warehouse workloads across multiple query engines and storage tiers.Watsonx.data supports a range of fit-for-purpose query engines, including Presto, Spark, Db2 and Netezza, which dynamically scale up and down to drive analytics costs down.

Users can store vast amounts of data in vendor-agnostic open formats, such as Parquet, Avro and Apache ORC, and share a single copy of data across multiple query engines using Apache Iceberg table format and shared metadata.

The tool includes semantic automation to help users discover, augment, refine and visualize watsonx.data and metadata through the power of watsonx.ai models.

Watsonx.data enables enterprises to build, train, tune, deploy and monitor trusted AI models for mission-critical workloads with data in the lakehouse and ensure compliance with lineage and reproducibility of data used for AI.

Watsonx.data helps streamline data engineering, reduce data pipelines, simplify data transformation and enrich data for consumption using SQL, Python or an AI-infused conversational interface.

Finally, Watsonx.data enables enterprises to support self-service access for more users to more data while enabling security and compliance with centralized governance and local automated policy enforcement.

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WatsonX.data by IBM was manually vetted by our editorial team and was first featured on May 11th 2023.
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Pros and Cons

Pros

Optimized for all workloads
Shared metadata layer
Open, hybrid, governed data store
Reduces data warehouse costs
Supports multiple query engines
Stores data in open formats
Single copy of data shared
Semantic automation included
Compliance with lineage and reproducibility
Streamlined data engineering
Simplifies data transformation
Enriches data for consumption
Self-service access enabled
Centralized governance and automated policy enforcement

Cons

Lack of real-time analysis
Vendor-agnostic formats only
Limited query engines compatibility
Complicated transformation procedure
Compliance with only Watsonx.ai models
Limited support
No dedicated mobile application
Usage can be complex for beginners
Costly for small businesses
No inbuilt visualization tool

Q&A

What is WatsonX.data?
What are the main features of WatsonX.data?
What is the purpose of the shared metadata layer in WatsonX.data?
How can WatsonX.data help reduce data warehouse costs?
What types of query engines does WatsonX.data support?
In what formats can data be stored in WatsonX.data?
What is semantic automation in the context of WatsonX.data?
How does WatsonX.data enhance data trust?
Can WatsonX.data be used to train AI models?
What are the compliance features offered by WatsonX.data?
How does WatsonX.data streamline data engineering?
How does WatsonX.data promote self-service access to data?
What security measures are in place for WatsonX.data?
Can WatsonX.data integrate with existing data analytics tools?
What languages can be used for data transformation in WatsonX.data?
How does WatsonX.data enable scalable analytics and AI?
What kind of data management capabilities does WatsonX.data support?
How does WatsonX.data connect to data sources?
How does WatsonX.data support AI and machine learning at scale?
How can enterprises use WatsonX.data for business intelligence?

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