Consumerization of BI: Data Visualization Competency Center

What do users want? Self-service, interactive analytics with all kinds of datasets with instant response times, no waiting.

Today there is a strong move towards “Consumerization of BI” as business users are demand the same speed, and ease of use from their enterprise applications as their at-home software.

Consumerization of BI (“data at your fingertips”) means:

• Help employees see and understand data
• Helping employees gain insight into their data using simple drag-and-drop operations to solve business problems
• Ability to quickly change filters and query conditions and conduct top down analysis via drill down
• Make analytics fast, easy, interactive, and most importantly – useful

In every major corporation there is a renewed push to industrialize and improve data visualization and reporting capabilities.

The challenge is not in procuring the next greatest tool or platform but how to organize the people, process and assets effectively to create value, reduce training and support costs.  In other words, how to facilitate and create a flexible operating model for data mining and visualization delivery that provides discipline at the core while giving the business the agility that they need to make decisions or meet client needs?

Decision making is a core business activity that requires facts and insights. Slow, rigid systems are no longer useful enough for sales, marketing and other business users or even IT teams that support them. Competitive pressures and new sources of data are creating new requirements. Users are demanding the ability to answer their questions quickly and easily.

So the new target state is to empower business users along the Discover, Decide and Do lifecycle:

• Discover new insights by rapidly accessing and interrogating data in ways that fit how people naturally think and ask questions.
• Decide on best actions by publishing dashboards, collaborating with others, discussing insights and persuading others through data presented in an interactive application (“app”) rather than in a static view.
• Do what is best at each decision point with confidence, based on the consensus that develops when new data is aggregated and explored with multiple associations and different points of view. Teams can take action more rapidly and move projects forward more effectively when everyone understands the data underlying decisions.

The challenge for business users is data discovery and ease-of-use. They want to focus on business questions that require aggregation and visualization. They want the interactive ability to quickly change filters and query conditions.

The challenge for infrastructure and application teams in every corporation is to deliver new easy-to-use platforms to their business partners quickly and consistently while maintaining governance and control.

To meet both sets of requirements, best practice firms are creating Data Mining and Visualization Competency Center or Centers of Excellence (DV-CoE) to ensure that the people, process and technology investments are not duplicated and addressed in a way that maximizes ROI and enhances IT-Business partnership. I have seen many cases where not having a proper structure leads to redundant projects and sub-optimal results.

2015 Year in “PreReview” in Technology

The summer of 2015 marked the release of the blockbuster Sci-fi movie, “Terminator Genisys,” which grossed a record $350 million at the box office and further popularized the notion of time travel. In addition to sequels and prequels, Hollywood has now adopted plots for movies in which the audience can choose among alternate storylines and follow them to their logical conclusion. The future, as we know it, is plural. This year in our PreReview of 2015, we once again present a few alternative scenarios for the future from our vantage point at the end of 2014.

New business models created by emerging technologies and unforeseen partnerships dominated the headlines in 2015.  Trending technologies such as the Internet of Things approached half the level of big data during 2015. Trending terms in the mainstream media such as drones and Bitcoin scored high in Google trends.

Here are three headlines from 2015 that caught our attention.

FedEx launches “parcelopter” service for 50-minute delivery 

Multi-channel to Omni-channel Retail Analytics: A Big Data Use Case

MULTI-CHANNEL is simply having multiple channels through which you buy, market, sell, and fulfill.

CROSS-CHANNEL has the ability to see all of a customer’s information across all channels enables more personalized offers based on their brand relationship.

OMNICHANNEL weaves all the touchpoints of the products and services of the brand into a  seamless fabric  of all phases of the  customer’s brand experience.

Which one are you?

Let’s face it – The old uni-channel retail model is dying in some cases and changing in others.  E-commerce is driving nearly all retail growth. Digital customers want simple, consistent, and relevant experiences across all channels, touchpoints, mobile screens, smart watches and other devices.