Accelerate your analytics transformation journey with IBM data management solutions
The opportunity to work with many clients on their analytics journey inspires us to achieve even greater heights with our solutions. The findings of the recent Forrester Wave: Data Management for Analytics, Q1 2023 is a clear indication that IBM continues to be a leader in analytics, providing our customers with innovative and fully integrated solutions.
Our purpose-built data technologies support end-to-end management of transactional, operational, and analytical data, without the complexity and security risks of moving or duplicating data. With the amount and types of data rapidly expanding, the ability to support any type and workload through our integrated platform allows customers to tackle complex analytics, BI, and ML/AI use cases with ease. Our customers also have the choice of running our analytics data platform in their cloud of choice, with options for self-managed or fully-managed SaaS services. SaaS deployments for IBM Db2 Warehouse are available on IBM Cloud and AWS, and Netezza Performance Server on Azure and AWS (tech preview), with more to come in 2023.
Let’s look at IBM’s take on some of the specific strengths recognized in Forrester’s Wave below. As noted in the report:
“IBM’s comprehensive DMA foundation supports multiple personas…IBM excels in data modeling, data integration, data transformation, data access, data security, data governance, in-platform analytics, and streaming data.”
Integrated analytics platform
IBM’s data warehousing and analytics solutions, Db2 Warehouse and Netezza, deliver data where needed, whether on-premises or on the cloud, in near-real time. Our end-to-end data management, data fabric, business apps and insights architectures provide a unified and governed user experience with access to 70+ connectors for both IBM and popular 3rd party data sources.
Data integration and transformation
Db2 Warehouse and Netezza Performance Server can natively query most data types from within and outside the database. Analytics users can virtualize data by seamlessly integrating their data warehouse with Watson Query, and leverage DataStage as part of the data fabric to apply broad capabilities in dynamic data quality, cleansing, aggregation and transformation.
IBM accelerates governance and security initiatives with end-to-end integrated platform governance designed with deep policy enforcement and the ability to view full workflow activity history. The ability to enable automatic business term assignments to describe data used for analytics and AI, as well as manage policies, sets apart the data governance and privacy capability of IBM’s holistic data management and data fabric architecture.
Data streaming and real-time analytics
IBM’s data warehouses are built with capabilities for near-real-time ingestion of data to provide low latency analytics for business users. Organizations can run transactional, operational and analytic workloads using the same data format, avoiding the need to move that data to another database engine for analytics.
Our approach to analytics enables users to derive insights from data directly where it lives, avoiding more duplicated, stale and siloed data. Create, evaluate and predict with high-performance machine learning models directly inside your data warehouse. IBM’s BI and ML/AI tools such as IBM Cognos Analytics and IBM Watson Studio seamlessly integrate with our warehouse solutions to quickly build advanced ML capabilities, reports and dashboards on top of your analytical data.
IBM’s analytics services, like our cloud-native Db2 Warehouse and Netezza offerings, are built to easily scale a nearly unlimited number of compute nodes per cluster. Once you’re up and running, you have full control over how and when you choose to scale with completely de-coupled storage and compute with the option of block storage and infinitely scalable object storage (coming soon). Finally, our Q-rep service powers data warehouse cross-region disaster recovery with seconds-latency achieved.
Product and ecosystem strategy
“IBM’s superior vision focuses on simplifying data management across hybrid-and-multi-cloud and edge through advanced automation, data intelligence, and self-service.”
Forrester Wave: Data Management for Analytics, Q1 2023
Our vision for analytics and AI is built on the premise that data needs to be managed differently. Organizations are facing many challenges with data leading to higher costs and preventing many from making use of this data. These complexities coupled with increasing regulation and ethics standards, will push enterprises to drive higher levels of data security and governance to share and access data, regardless of where data lives. We believe the industry awaits a breakthrough opportunity for organizations that want to significantly reduce cost, simplify data access, and automate unified governance to scale analytics and AI, anywhere.