The BI Journey: Do You Know Where You Are?
With the explosion of structured and unstructured data and affordable technologies to handle it all, the importance of choosing the right Business Intelligence (BI) for Big Data has never been greater. With the ability to sort, store, and analyze data, enterprise is able to maximize its data investment with Business Intelligence. In this blog, I will help you to navigate your journey through BI options to find the right match for your needs.
BI has been around for decades — from the inception of data processing systems to today’s fascination with predictive analytics. Its development is an evolving journey of increased data insight, supported by new means of capturing data (including big and unstructured).
As the old adage goes, “How do you know where you are going if you do not have a plan to get there?” Drawing on this question, Corporate Technologies has adopted a planning framework, BI Maturity Curve, to guide the BI journey for Big Data. The BI Maturity Curve helps to benchmark where you are in your BI journey and align your business initiatives with the BI to achieve them.
The BI Maturity Curve is the intersection of business impact and the well-defined stages of BI. Where your organization is on the BI Maturity Curve is determined by the business value your organization derives from BI. To move up the curve, you need increasingly sophisticated and robust data, technologies, processes, and IT and business skills.
The BI Maturity Curve stages are:
Operational BI: The primary business value is a dated or real time view of “what’s happening” delivered through static reports and dashboards. The data tends to be confined to that in readily accessible operational systems for a defined period of time.
Traditional BI: This stage typically incorporates multiple, and sometimes disparate, data sources that provide a more in-depth and broader view of “what’s happened” over extended period of time. The ability to normalize and integrate related data and present it to business users in an intuitive format provides the incremental business value.
Data Mining: This stage is characterized by the application of more powerful analytic techniques to rich data sets to address “why did it happen.” Data Mining is primarily used to conduct one-off analyses and insights to guide strategic decision-making.
Predictive: This stage is the “holy grail” of BI, marrying multiple data sources and analytical tools with lightning fast processors and data bases to enable real-time decision-making. It helps to forecast “what will happen.” The availability of data at the “moment of decision” and reliability of the predictive models determines the business impact of predictive analytics.
We have blogged on each stage of the BI Journey and we invite you to follow the hyperlinks above to learn more about the specific assets and capabilities in each stage. Each stage encompasses: data, technologies, processes, business, IT staff and skills.