Best Data Management Software for IBM watsonx Assistant

Every model requires governance to ensure ethical and responsible decision-making in the business. IBM® watsonx.governance™ toolkit for AI governance allows you to direct, manage and monitor your organization's AI activities. It uses software automation to enhance your ability to mitigate risk, manage regulatory requirements, and address ethical concerns when it comes to both generative AI (ML) and machine learning models. Access automated and scalable compliance, governance and risk tools that cover financial management, IT governance, IT governance, operational risk and policy management. Proactively detect model risks and mitigate them while translating AI regulations to enforceable policies that can be enforced automatically.

The data refinery tool is available in IBM Watson®, Studio and Watson™, Knowledge Catalog. It transforms large amounts of data quickly into useful, high-quality information that's ready to be used for analytics. Over 100 built-in operations allow you to interactively search, cleanse, and transform data. No programming skills are required. You can easily analyze the distribution and quality of your data with dozens of built in graphs, charts, and statistics. Automatically identify data types and business classes. Access and explore data from a variety of data sources within your organization, or in the cloud. Data governance professionals can automatically enforce policies. For repeatable results, schedule data flow executions. Receive notifications and monitor results. Apache Spark allows you to easily scale out and apply transformation recipes to full data sets. No need to manage Apache Spark clusters.

You can build, run, and manage AI models and optimize decisions across any cloud. IBM Watson Studio allows you to deploy AI anywhere with IBM Cloud Pak®, the IBM data and AI platform. Open, flexible, multicloud architecture allows you to unite teams, simplify the AI lifecycle management, and accelerate time-to-value. ModelOps pipelines automate the AI lifecycle. AutoAI accelerates data science development. AutoAI allows you to create and programmatically build models. One-click integration allows you to deploy and run models. Promoting AI governance through fair and explicable AI. Optimizing decisions can improve business results. Open source frameworks such as PyTorch and TensorFlow can be used, as well as scikit-learn. You can combine the development tools, including popular IDEs and Jupyter notebooks. JupterLab and CLIs. This includes languages like Python, R, and Scala. IBM Watson Studio automates the management of the AI lifecycle to help you build and scale AI with trust.

To identify the best actions, you need to build and solve complex optimization models. IBM®, ILOG®, CPLEX®, Optimization Studio uses decision optimization technology. It optimizes your business decisions, creates and deploys optimization models quickly, and creates real-world applications that can significantly increase business outcomes. How does it work? How? It combines a fully-featured integrated development environment that supports Optimization Programming Language, (OPL), and the high-performance CPLEX/CP Optimizer solvers. It's data science for your decisions. IBM Decision Optimization is also available in Cloud Pak for Data. This allows you to combine optimization and machine-learning within a unified environment, IBM Watson® Studio that enables AI infused optimization modeling capabilities.