Is Your Data Ready for AI?
Analytics products and services can discover meaningful patterns in data that reveal insights that organizations can interpret and communicate to others.
This week, I start a focus on analytics solutions. These products and services are used to discover meaningful patterns in data that reveal insights that organizations can interpret and communicate to others. Employing a product or solution may be more complex and challenging, especially if data isn’t ready for new uses like AI. Let me start with a survey of the analytics landscape.
The Main Idea
There are different kinds of analytics like business analytics or big data. Let’s start simple. What is business analytics? According to IBM, business analytics is “a set of automated data analysis practices, tools and services that help you understand both what is happening in your business and why, to improve decision-making and help you plan for the future.”
How big is the analytics market? Businesswire reports that the research firm Technavio has recently released a report on the analytics market where they anticipate incremental growth of $109.71 billion between the years 2020 and 2024, progressing at a CAGR of almost 14%. Most of this growth is likely to originate from the United States. They report that one of the key drivers is the growing complexity of data.
Products, Solutions and Services
If analytics was a simple area, we might think in simple ways. We could be tempted to think that some organizations buy products whereas others buy solutions or services. It’s not that straightforward because data, the target of analytic actions, has diverse origins, residence, history and uses. A mix of approaches is often a more realistic outcome for many customers. Let’s consider three questions about analytics offerings.
1. What can you expect from an analytics product?
Products can be best appreciated as having a way to help organizations achieve results. IBM has a useful model that applies to its different analytics products that can help frame a product discussion.
| Focus | Description |
| Modernize | This includes products that make data ready for AI, hybrid cloud or both. |
| Collect | This includes products that make data simple and accessible, especially with AI and cloud support. |
| Organize | This includes products used to create a business-ready analytics foundation. |
| Analyze | This includes products that help scale AI everywhere with trust and transparency. |
| Infuse | These products help operationalize AI throughout the business. |
This is a helpful way to rationalize IBM’s diverse set of products that drive analytics adoption and use in organizations.
2. What can you expect from an analytics solution?
Analytics solutions can be used to infuse AI to make data ready for a variety of strategic uses. Successful implementation of use cases, like the ones discussed below, are often brought about through consulting engagements:
| Strategic use case | Desired outcome |
| Prepare for data privacy regulations | Accelerate readiness for data privacy regulations like General Data Protection Regulation |
| Create a governance strategy | Designed to provide clean, reliable, business-ready data to all data consumers within the organization |
| Simplify enterprise data offloading | Used to build an analytics foundation with improved data quality, integration and governance to improve insights with trusted data |
| Help improve fraud detection | Increase an organization’s ability to thwart cybercriminals through improved predictive insights and real-time analysis |
| Transform customer experience | Provide a much richer context and deeper insight to help predict customer behaviors, patterns and trends |
These use cases are implemented by deploying solutions organized by purpose that include:
- Data integration to transform structured and unstructured data on any system supporting a scalable big data platform
- Data quality to cleanse, manage and make available reliable data across an organization
- Data governance to administer both structured and unstructured data to manage compliance risks
- Data replication to deliver real-time data to derive better insights
- Master data management so business and IT users can collaborate and innovate with trusted master data across the organization
- Information lifecycle to lower costs and manage risk while supporting compliance
Analytics solutions are the connection between uses (use cases) and outcomes that drive results. Although often rooted in products, solutions typically have specialized elements beyond software that include drivers like security or compliance expertise.
3. What can you expect from an analytics service?
The main goal of an analytics service is to accelerate an organization’s business transformation. Specialized skills supplied through a service help achieve fast results by guiding customer teams through projects as varied as validating use cases with ROI to helping with deploying and implementing an analytics data lab. Utilizing fee services is a proven way for organizations to develop their in-house skills and get a jump-start on their strategic projects.
The domain of analytics projects is so broad that companies that provide these services organize what they do in a content of offerings. An analytics offering typically has a framework, scope, plans, typical work products and a team structure. That isn’t to say that the service is one-size-fits-all, but having a strong definition and a track record of proven outcomes is necessary to compete in this marketplace.
Next Week
Next week, I’ll explore analytics thorough the lens of specific IBM analytics products.