icon_CloudMgmt icon_DollarSign icon_Globe icon_ITAuto icon_ITOps icon_ITSMgmt icon_Mainframe icon_MyIT icon_Ribbon icon_Star icon_User icon_Users icon_VideoPlay icon_Workload icon_caution icon_close s-chevronLeft s-chevronRight s-chevronThinRight s-chevronThinRight s-chevronThinLeft s-chevronThinLeft s-trophy s-chevronDown
BMC

In the Autonomous Digital Enterprise, a Data-Driven Business uses artificial intelligence (AI) and analytics to extract and monetize valuable data from traditional sources like records and new sources like Internet of Things (IoT) devices, social media, and customer engagement systems.

What Is an Autonomous Digital Enterprise?

The Autonomous Digital Enterprise is a forward-looking view of the future state of business, one in which agile, customer-centric, insight-driven companies evolve their operations to survive and thrive in the midst of persistent disruption. The Data-Driven Business is one of five technology-enabled tenets that galvanize and sustain the Autonomous Digital Enterprise.

Autonomous Digital Enterprise
Current Business Challenges

Current Business Challenges

Forbes estimates that by 2025, more than 150 zettabytes of data will need analysis*, yet Accenture found in a recent survey of 190 U.S. executives that 81 percent of companies lack an enterprise data strategy to fully capitalize on their data assets.** There’s a reason for that lag. Getting your arms around all that data and using it to grow your business can present an array of challenges, including:

  • Multiple teams, tools, processes, and sources of upstream and downstream data
  • High failure risks, inability to scale, and difficult governance
  • Expensive, inefficient monitoring and controlling capabilities
  • Managing constant data streams fast enough to meet customers’ performance expectations
  • Ensuring optimal performance and availability for existing services while continuing to innovate

How Technology Helps

The technology behind the Data-Driven Business includes AI and machine learning (ML) integrated with automation tools. Working together with human expertise, they combine to:

  • Convert raw data into insights and actions
  • Monetize data with insights, bartering, brokering, and business intelligence
  • Ensure data compliance with data quality best practices
  • Protect privacy with governance tools
  • Automate workflows for improved visibility and control of the entire data pipeline
  • Leverage predictive analytics to ingest, store, process, collect, and analyze data
  • Use performance, management, recovery, and cost optimization solutions to keep mainframe-based applications running 24x7
How Technology Helps
Data-Driven Business

Solving Business Challenges

We’ve identified select business use cases where a Data-Driven Business can solve for these challenges. Download the e-book to learn more.

Talk to us about becoming an Autonomous Digital Enterprise