Why IBM for data warehouse offerings?

 IT groups today need a new approach to data warehousing — a modern one that enables them to respond rapidly to requests for analytic resources from business groups without increasing costs or complexity. For many IT groups, a hybrid data warehouse environment is the answer. A strong data warehouse structure is embedded with blend of technologies and components which aids strategic use of the available data.

Highlights on what IBM Data warehouse solutions can bring into a client’s table:

  • It facilitates quick deployment of integrated and elastic cloud data warehouse services and simplify client’s journey to the cloud.
  • Continuously meet service-level agreements (SLAs) by adjusting workloads across cloud and on-premises data stores.
  • Enable self-service access and facilitate analysis of large data volumes through in-database IBM® Netezza® and Apache Spark analytics.

Features

Icon representing the flexible licensing options for IBM’s data warehousing offerings

Flexible licensing

With multiple licensing and configuration options available, IBM has the flexibility to meet your data warehousing needs as they evolve over time. It offers the ability to easily and cost-effectively store and analyze your data where it is best housed.

Icon representing the easy scalability of IBM’s data warehousing offerings

Adaptable scaling

Elastic pricing for data warehousing on IBM Cloud™ enables you to independently scale storage or compute capacity easily and quickly. By choosing a scalable cloud solution, you pay only for the capabilities you need at any given time.

Icon representing the capability of IBM’s data warehousing offerings to provide a foundation for data insights

A foundation for insight

Build a strong foundation for data insights with a data warehouse solution that can handle structured and unstructured data, run apps and queries in languages you already know and integrate existing systems with new capabilities.

Featured product

IBM Integrated Analytics System

IBM Integrated Analytics System drives the insights needed to maintain your competitiveness by matching accelerated development and deployment times for your data scientists with a high-performance, optimized and cloud-ready data platform.

Related solutions

IBM Db2 Big SQL

A data virtualization tool that helps you access, query and summarize data from nearly any platform, including databases, data warehouses, NoSQL databases, and more. Concurrently exploit Apache Hive, HBase and Spark using a single database connection — or even a single SQL query.

IBM Data Science

A configured, collaborative, cloud-based analytic environment that includes IBM value-adds, such as managed Spark. Use a single workspace for your tools, but collaborate and share projects as needed. Analyze data using RStudio®, Jupyter and Python.

IBM Db2 Warehouse on Cloud (formerly IBM dashDB® for Analytics)

A fully managed, flexible cloud data warehouse with in-memory IBM BLU Acceleration® and built-in Oracle and IBM Netezza compatibility designed to help you get faster insights. IBM Db2 Warehouse on Cloud is managed, monitored, encrypted and backed up by IBM, so you can focus on data analysis instead of administration.

 

Resources

Data warehouse platforms, demystified

Today’s complex analytics workloads require more than strong performances. This ebook explores the pros and cons of each data warehouse platform option that optimize analytics results. An integrated data warehouse platform can give you agility and scalability of cloud in your data center.

Webinar: Do data science faster with the IBM Integrated Analytics System

 In this webinar you will learn more about the built-in data science tools, the Common SQL Engine and how machine learning and in-place analytics are the keys to helping you accelerate your competitiveness.

 

Delivering Hybrid Analytics at the speed of Business: IBM Integrated Analytics System

This whitepaper discuss in detail why organization should not hesitate to embrace a hybrid cloud environment that can deliver high performance through its purpose-built database system and in turn can lead to powerful analysis and rapid decision making.

 

TDWI Checklist Report: Data Warehousing in the Cloud

TDWI offers a strategic approach to choosing the right data warehouse solution for your organization, outlining seven best practices for assessing your analytic needs, determining which solution offers the best value and achieving analytic insights.

Client case studies

How AMC uses machine learning to find out more about TV viewers

Machine learning is a hot topic no matter the industry, and rightfully so. Many see it as a path to greater efficiency and deeper insights. AMC has established a data foundation for AI and machine learning with IBM data warehouse offerings.

Genpact

Genpact consolidates its departmental data by accelerated reporting and fine-tunes business planning with self-service analytics.

Valor Holdings

Learn how Valor Holdings Co., Ltd., achieves dramatically improved performance by moving a database of over 10 billion customer transactions into the cloud. The company also gained a robust and well-supported data platform with IBM Db2 Warehouse on Cloud.

Partners

Sparkflows

This drag-and-drop environment for developers enables Spark-based analytics and machine learning on large data sets, such as those contained in IBM Db2. Sparkflows helps you analyze and present data quickly and includes tools for rich visualizations of big data.

Aginity Workbench

IBM Db2, when combined with Aginity Workbench, provides a platform that’s easier to use, delivering both analytics and warehousing-as-a-service. This solution uses the best of IBM technologies: in-memory computing with BLU acceleration, the power and simplicity of embedded analytics, and the powerful infrastructure of IBM Cloud.

Engage with an expert

A no-cost, one-on-one call with an experienced IBM expert.
Get answers on why, when and how to use a data warehouse and the best platform for your needs.