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IBM watsonx.data

Score8.4 out of 10

63 Reviews and Ratings

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What is IBM watsonx.data?

Watsonx.data is presented as an open, hybrid and governed data store that makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.

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Who Buys & Uses IBM watsonx.data

IBM watsonx.data Reviews

What users are saying about IBM watsonx.data.
View all IBM watsonx.data reviews

Pros

  • Robust data integration across diverse sources and environments
  • Open lakehouse architecture for flexible data management
  • Strong performance with big data workloads

Cons

  • Perceived complexity and lack of maturity
  • User interface needs improvement for non-technical users
  • Slow data importing processes due to chunking

IBM watsonx.data

Incentivized
Murali MadhanagopalView profile
Architect in Engineering at Intel (201-500 employees)

Use Cases and Deployment Scope

IBM watsonx.data data for lakehouse creation and consolidation of data. Use differrent data sources import features

Pros

  • vector db
  • Ai ready
  • watsonx.ai integration
  • wx.orchestrate integration

Cons

  • better llm support
  • insights generation
  • open source support

Return on Investment

  • fast and easy
  • easy install
  • integration with other AI tools

Alternatives Considered

AWS Elastic Beanstalk and Apache Kafka

Other Software Used

Amazon Elasticsearch Service, Apache Kafka

Usability

IBM Watsonx.data Next Gen Data Lake Platform

Incentivized
Lalit GoelView profile
Deputy Manager in Information Technology at TV Today Network Limited (501-1000 employees)

Use Cases and Deployment Scope

For Storing and managing large data for BI and Analytics, its supports Hybrid mode so it is the right platform.

Pros

  • Open architecture, Hybrid mode (can use on-prem or on cloud)
  • Fully compliance to meet governance
  • Multi Engine support

Cons

  • Complex for every user in terms of ease of use
  • IBM is known to pricy solution, so price remain the primary concern for most of the organisations.

Return on Investment

  • Less ROI , because of high prices
  • Although this meets the primary objective of handling all data at single place, which helps faster developments and reduce data duplication
  • Fulfill governance & security with built-in features , one can use for access control and policy enforcement.

Alternatives Considered

Azure Databricks and Snowflake

Other Software Used

Canva, Tungsten Capture, Zimbra by Synacor

Accessing Distributed data is simpler with watsonx.data

Incentivized
Verified User
Analyst in Information Technology (51-200 employees)

Use Cases and Deployment Scope

I use IBM watsonx.data to organize and analyze data from various sources. My core use case for this platform is to run queries to retrieve and manipulate data, create reports, and analyze client assets. It solves the problem of accessing data from different storage locations and sources and managing it all in one place.

Pros

  • It makes accessing data easy and fast from various sources.
  • I work with SQL, and its SQL-based querying makes it a comfortable approach to use.
  • It can handle large data sets easily, and analysis is quicker as I don't have to move data since I can just access it from any source.

Cons

  • Interface do need some improvement to be more intuitive for analysts like me.
  • Configuring multiple data sources can require support, as it isn't easy for new users. So, it can be made easier.
  • Additional ETL features can be added, so users don't have to switch between tools.

Return on Investment

  • It has reduced the time it takes me to locate and access the data. Which consequently increased my productivity.
  • Data preparation is also easier because I can now access data from one place, which has saved me a lot of time.
  • I don't have to completely redesign workflows as more data grows, so they're easier to manage.

Other Software Used

AT&T Workforce Manager, AT&T Data Center Outsourcing, General Datatech (GDT)

My Fair Opinion

Incentivized
Verified User
Engineer in Engineering (1001-5000 employees)

Use Cases and Deployment Scope

We use IBM watsonx.data as an AI assistant to accelerate troubleshooting and incident analysis. When batch jobs or automation rules don't work as intended, my team is usually the one that gets sent the ticket to do the research and investigate why it happened. Combing through logs to find a needle in a haystack is a tedious process that sometimes takes multiple sessions across multiple days to find that one line that tells you why everything failed. Sometimes you find the needle and don't even know that you've found it because you can't know everything about the mainframe. So having a tool that can help lead me in the right direction is something I rely on heavily.

Pros

  • Sometimes when I provide it a line from the log to get an explanation, it can provide an explanation that I didn't find on the web. Sometimes that explanation is what puts me going in the right direction.
  • It's best for business to have tickets to resolved with a working solution as soon as possible. This reduces the time I need to properly research what went wrong.

Cons

  • If it also helped me troubleshoot OPS/REXX code it would be the only tool I used.
  • I'd like for more accurate diagnoses from the system but maybe it just needs more user activity to get better.

Return on Investment

  • It definitely saves my time. It provides me with an answer that I can't find from the web sometimes so I'm able to gather more research before presenting anything to my teammates.

Alternatives Considered

Anthropic Claude

Data Data everywhere.

Incentivized
Verified User
Director in Engineering (10,001+ employees)

Use Cases and Deployment Scope

As a Distributor, we have wastsonx.data in our Digital Innovation Center, where we use it for Presales and Partner enablement. We also use it for demo labs and PoC environments. It is used to validate use cases, test architectures, and build solution designs. We allow business partners access so they can set up and test their own real-world solutions and expand their portfolio of solutions and services.

Pros

  • It is an open-source architecture with open data formats.
  • Flexibility of data sources and locations (cloud, on-prem, hybrid).
  • Combining structured and unstructured data for a wide range of workloads.

Cons

  • Improvements in simplicity/maturity of data integration capabilities.
  • Simplify transformation and orchestration processes.
  • It could use some canned templates for redundant/repetitive operations.

Return on Investment

  • Helps is get more partners certified and enabled leading to more deals.
  • Helps us conduct more PoC's and demos without bearing additional costs.
  • Allows us to claim true "offering leadership". differentiation, and value added for our partners and their customers.

Alternatives Considered

Databricks Data Intelligence Platform, Snowflake and Amazon Redshift

Other Software Used

Atlassian Jira, Microsoft 365, Microsoft Power BI, Microsoft Power BI Embedded

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