As we learned fromArt Krulish on Tuesday, omni-channel marketing presents a set of new challenges for retailers--and their data warehousing professionals.<Click>Today’s highly-connected marketplace offers more choices, which makes understanding customers more important than ever. And customers realize this too. In fact, many are now expecting companies to cater to them like never before.<Click>Smart devices and social media sites have up opened up new ways for customers to interact with retailers. The result is spreading customer interactions across many channels. A key task for data professionals is to figure out which channels contribute most to a reliable view of their customers.<Click>And with these new channels comes lots and lots of data. Some of the data may come in semi-structured forms that are unfamiliar to the data professional. Figuring those out, and the cost of processing large volumes of it, makes it critical for data professionals to be certain they are crunching only the data that will improve customer insights.<Click>Some of this information is fleeting. If I stop in at a coffee shop, I’ll be in the area long enough to log onto WiFi, check-in on Facebook, and drink my latte—then I’ll be off. If I get an offer that night to check out the gym next door, it’s probably too late. Unless I visit that coffee shop several times a week. Detecting patterns in customer behavior separates the noise from real opportunity. <Click>But in order to get to those trends, we need both short and long term views—in short we need an enterprise view of the customer.
<Click>Using more data to understand your customers better is a good idea, but it isn’t cheap. And it isn’t simply a matter of calling your favorite vendor and ordering more hardware and software. Managing these kinds of high-volume sources will have significant technology implications for your origination: new infrastructure, new skill sets, and new timeframes for completing Herculean tasks are all part of the deal.A big help is having advanced warehouse management tools like Kalido, whose skill sets are abstracted from the underlying database platform and can easily be re-platformed when your data volumes ramp up. <Click>Another big help is a method of developing analytics that include business users. Involving them in the design process will ensure that investments in big data produce real operational value.<Click>
All of the different channels and varying levels of structure make it challenging to create uniformity in the data that describes customers—and apply a common set of business logic to it all. <Click>Unstructured and semi-structured data doesn’t lend itself to validation in its raw form; however, some semblance of structure must be applied to it eventually to be useful in analytics. <Click>All of this points to managing the business logic in a central repository—and the repository best suited to do that remains the data warehouse. <Click>Why? The volumes are typically to large for data virtualizaiton to be useful, and recent advanced in MPP hardware have made bringing data together, where it can managed centrally, the way to go.
The challenges and opportunities of Omni-Channel marketing have direct implications for the agile data warehouse. <Click>Customers are complex, and sometimes the rules organizations develop to understand them can get equally complex. Defining the business rules graphically makes them easier to manage and ensures consistent and correct interpretation—no matter what the source.<Click>And when those rules do change, Kalido makes changing them in the warehouse as simple as redrawing them on the screen.<Click>A common change is adding new data sources. As we know, there is no shortage of sources of useful data in an Omni-channel environment. Kalido makes it easy, so you don’t miss opportunities.<Click>Delivering analytics quickly is important to understanding your customers. Kalido helps by defining complex analyses—such as segmentation, automated summarization, data derivations and what-if—using the power of the warehouse application itself.<Click>And Kalido runs on the most powerful parallel database platforms in the industry, such as Teradata and Oracle Exadata, which makes big data volumes no trouble at all.<Click>But all the capability and processing speed in the world won’t deliver real, operational value if it doesn’t put information into the hands of the people who need it fast. That’s why Kalido provides data in a variety of formats. <Click>The warehouse isn’t going away in the omni-channel world. It will continue to play a vital role in supporting historical and cross-funcntional analysis of the data.<Click>
The Kalido information Engine is the first highly-automated, purpose-built environment for implementing agile data warehouses.Business modeling allows IT and business to speak the same language as they collaborate because the requirements and business rules are defined graphically and then automated by Kalido.And because a Kalido warehouse is highly automated, things move quicker in development by reducing etl coding, removing the need for unnecessary translations into to logical and physical models, as well as having developers make changes to the physical layer directly.Finally, Kalido delivers information in a variety of formats, including industry standard BI tools like Excel, Qlik View, Business Objects, Cognos and SSIS. Automating the BI semantic layer greatly reduces the time required to build reports, improving your reaction time to customer trends.Let’s take a few minutes for a brief demonstration of how an agile Kalido data warehouse can help an organization analyze its first online channel.
--Staging Layer Definition--Integration Layer DefinitionNext I’ll show the consumption layer definitionDemo deploying the Corp Demo Model--BIM (deploy)--Explorer (show then build att & map tables)--Open SQLServer and show tables?
(TD_DEMO_3)--Walk through the UID screens--Show the result modelFeel like it takes too long to generate the UID but am open to discuss.
The Kalido Information Engine offers many advanced capabilities, like:Comprehensive Hierarchy Support, which enables business and technical teams Express complex business relationships simply and graphically/History tracking and Audit, where Kalido maintains history of both the data AND the model. Kalido warehouse operations automation simplifies the process of automating loads, test switches and load dependencies in Kalido and move to scheduling toolThese capabilities make the Kalido Information engine the right warehousing platform for deriving the right analytics from your Omni-ChannelOrganization to fully understand your customers.Thank you for attending today’s event.