In the Modern Data World, Truth is Sometimes just an opinion...and Qlik Data Catalyst can help

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In a modern analytics world, people are asking more and more questions that do not have simple answers and require combining data in new and interesting ways.  What is best?  What is riskiest?  The future of analytics will require data literate analytics communities to argue with data.  And in order to do this, they need access to the data.  This is what Qlik Data Catalyst delivers.

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Data Warehouses were born of a finance and regulatory age.  When you peel away the buzz words, the principle goal of this initial phase of business intelligence was the certification of truth.  Warehouses helped to close the books and analyze results.  Regulations like Dodd Frank wanted to make sure that you took special care to certify the accuracy of financial results and Basel wanted certainty around capital liquidity and on and on.  Companies would spend months or years developing common metrics, KPIs, and descriptions so that a warehouse would accurately represent this truth.

In our professional lives, many items still require this certainty.  There can only be one reported quarterly earnings figure.  There can only be one number of beds in a hospital or factories available for manufacturing.  However, an increasing number of questions do not have this kind of tidy right and wrong answer.  Consider the following:

                                    Who are our best customers?

                                    Is that loan risky?

                                    Who are our most effective employees?

                                    Should I be concerned about the latest interest rate hike?

Words like best, risky, and effective are by their very natures, subjective.  My colleague at Qlik, Jordon Morrow (@analytics_time), writes and speaks extensively about the importance of data literacy and uses a phrase that has always resonated with me: data literacy requires the ability to argue with data.  This is key when the very nature of what we are evaluating does not have neat, tidy truths.

Let’s give an example.  A retail company trying to liquidate its winter inventory and has asked three people to evaluate the best target list for an e-mail campaign.

• John downloads last year’s campaign results and collects the e-mails of the 2% who placed an order.  He e-mails the list to his boss, thinking that past behavior is the best predictor of future behavior.
• Jennifer thinks about the problem differently.  She looks through sales records of anyone who has bought winter merchandise in the past 5 years during the month of March who had more than a 25% discount on the merchandise.  She notices that these people often come to the web site to learn about sales before purchasing.  Her reasoning is that a certain type of person who likes discounts and winter clothes is the target.
• Juan takes yet another approach.  He looks at social media feeds of brand influencers.  He notices that there are 100 people with 1 million or more followers and that social media posts by these people about product sales traditionally cause a 1% spike in sales for the day as their followers flock to the stores.  This is his target list.

This is good.  This is healthy.  And this relies on the availability of data.  That's where Qlik Data Catalyst comes in.  Qlik Data Catalyst is a solution that makes data from across the enterprise available in a single catalog with the ability to order and obtain information on demand.  For the data provider, this provides a simplified manner to organize data, apply security rules, and create meaningful descriptions and other metadata to increase consumption.  For the data analyst, it is the simple way to get your hands on the data that you need and even discover data that you did not know about.

Qlik Data Catalyst collects data from around the enterprise including big data sets and onboards them into a consistent format.  It profiles the data, tags data elements, allows for preparation of new analytics data sets, and makes all of this available in a secure self-service shopping experience.  This is the way that modern analytics has to work.  Businesses can no longer wait for months for the technology team to create a common physical model in a data warehouse.  Rather, people want data that is a little more raw and a lot more fresh with the ability to make it their own.  Qlik Data Catalyst calls this process getting data "from raw to ready".

Once this data is available, the sky is the limits.  Easily publish to Qlik Sense or to the analytics platform of your choice.

Qlik Data Catalyst is revolutionizing the supply chain of data for modern analytics.