Roadmap to the Data Gateway (Part 1 of 2)

>>>Roadmap to the Data Gateway (Part 1 of 2)

dataImplementation of self-service business analysis tools allows the Business users to wean themselves from the ever-so-busy Business Intelligence (BI) experts and explore the world on their own terms, by their own schedule. In this scenario, BI is no longer the gatekeeper of data, rather it is the gateway.

Considerations of the BI Team:

The notion of a new near real-time, multi-sourced analysis environment poses many obstacles for the BI team. How many disparate data sources are we to integrate? Will the current environment support the ambitions of the client? Do we have the right tools and enough horse power? What about the number of IT/BI resources to carry out both the development and maintenance? Finally, does the client have the budget to reconcile any shortcomings?

Considerations of the Business Team:

The Business must be able to not only set trends, but identify trends in an instant. Mounting pressure exists as a result of the fast-pace changes and it must ride ahead of the storm and essentially recalibrate and remold its models on the fly. It is at the mercy of the offerings and schedule of the BI team. With the gateway opening to visualization and analytics reporting solutions, the Business can begin to take control.

In this 2 part series, we’ll explore the BRAT thought process for building a solid roadmap for Gateway success. For the purpose of this article and to emphasize one united front, I define the BI team as the conglomeration of both the BI and Data Warehousing (DW) teams, often separate resources with equal value.

Blueprint

Buzz words like Hadoop, big data and real-time analysis keep you up at night. You envision your company leading the way in the world of high-tech data analysis or at the very least, catching up to the modern world.

Strategic and collaborative planning at the outset where the purpose and mission is clearly defined will prove to guide you with precision through this project marathon. Not unlike building contractors, the more time spent to perfect your blueprint upfront, the more it will deliver cost-effectiveness and time-savings.

Clearly identify all project stakeholders and backups, requiring full participation. All stakeholders should be present during all decision-making meetings to ensure awareness of direction and necessary diversions.

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Defend the Need:

The starting point for any successful roadmap is to define the “why.” Dedicating time up front to justify the investment and secure buy-in is essential to the success of the project. Why must your company invest in revamping its BI environment? Is it simply too clunky and slow to ever attain the competitive edge it needs? Do several versions of the truth exist at any one meeting leaving everyone bewildered and leadership distrusting? This situation arises when analysts reveal variations in results due to different methods of calculating the answer. Are the right questions asked, but not answered with confidence and in a time efficient manner? As an example within the retail industry, your goal in the next two years is to increase customer retention by 15% as well as to increase profits per store by 10%. You do not have one central repository in which to gather and analyze the data.

List the Success Factors:

In order to lay a proper foundation, you must detail the “what” prior to even considering how to approach the effort. What questions must be answered to achieve the success you’re seeking? Let’s remember the project is all about data, not tools, at this point. Determine what data would help deliver your goals if you had it more accessible and more measurable. Make
a must-have list of all Key Performance Indicators (KPI) you will need.

You must dive into the Customer Relationship Management (CRM) data and design a plan to increase customer retention. Data has been collected as a result of customer loyalty programs through the CRM system. As well, your directive is to analyze the data pertaining to each retail store’s sales per square foot and to isolate ways in which sales can be increased within
each store. A separate system contains store location attributes such as square footage, addresses, and price point categories (discount, mid-range, high end).

Define the Requirements:

Now that you’ve pinpointed the need and outlined the must-haves, it is time to dive into “how” to reach success from a business perspective.

In order to lead the market, you must be able to analyze in near real-time. You also must be able to set your analysts free to build their own data mining tools and analysis while enforcing company-wide business rules and standards. Finally, you must be able to report against several databases.

Following are common issues and approaches.

Resource Limitations

Accurately assessing cost is highly dependent on evaluating the existing environments from which data will be sourced.

The BI team is hard at work resolving issues, requests for information, and new requests. The business is working tirelessly to meet its goals and in doing so, is dependent on the support of the BI team to create additional and easily comprehensible reports. In order to meet the high-demand deadlines, the BI team finds itself taking an increasing number of shortcuts that, one by one, do not appear harmful. These time-saving shortcuts include stitching solutions together without regard to best practice and neglecting the critical task of documentation.

When integrating external sources into one central Data Warehouse environment, the BI team must first contend with the states of each data source in order to understand the inner-workings of the silos of sub-systems and extract pertinent data. Where best practices and standardization have taken a back seat, the sub-systems have layers of unnecessary complexity and no documentation with which to easily maneuver. An exorbitant amount of time must be taken to navigate the network of confusion.

During the course of implementing a new project, time must be allocated to properly document the new integrations as well as existing gaps between requirements and available data. Limitations in resources to carry out the development may certainly hinder this initiative. Taking shortcuts by bypassing these critical deliverables is a definite risk to the project in
terms of long-term maintenance and short-term development as described above.

For instance, creating a comprehensive “source to target mappings” document wherein the sources of all data are defined along with the tables and fields within the new data warehouse will allow for easier research and development providing an instant cross-reference. It will also bring to light those data points that are either non-existent or not readily accessible.

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We have now defined the why, what, and how of roadmap development. Next week we will learn how to bridge the gaps between the Business and BI teams, proper tool selection, and merging all the data together into one central repository.

Angel S. Kahmar is a Senior Consultant at SDLC Partners, a leading provider of business and technology solutions. Please feel free to contact Angel at akahmar@sdlcpartners.com with any questions on this blog post or to further discuss Business Intelligence.