What is data modeling or architecture? How does one go about achieving it? Well data consolidation in the bringing together of all data points from multiple data sets into a single master database or MDM tool to create a single, unified view of the data. The value in bringing together siloed information from multiple systems into one is a clear picture of what is happening in an organization. The warehouse team can clearly see the inventory and has to confirm for the procurement team what they need more of or don’t while the sales team has to push products based on what customers are buying. What is your businesses exposure to each customer you’re selling to? All of this can be found in unifying the data sets from the many tools you are already using.
The first step in consolidating your data, is to profile the information from each system. This means you identify what each data set contains and how it is used by the end user and what the data means for the business. Next, you identify the data model you will be using, which will include a variety of details like taxonomy, governance, policy and similar details (we will cover more on this in a future article). After this step, you move on to the architecture which will be how your systems connect and the hierarchy of the data sets and the relationships that need to exist for the appropriate workflows to be leveraged for the data in your golden records to maintained by the MDM and not just visible.
Once you complete this planning and effort, you can move forward with implementing the planned model and architecture using a strong MDM tool, we highly recommend Semarchy xDM. It is the most intelligent MDM on the market with new advances coming all the time. The MDM tool you select is critical because it needs to be agile and versatile for all of your various data sets, human resources, finance, project management, inventory, CRM, automated marketing, to name a few. Data projects should endeavor to be long lasting and constantly evolving for the business strategy and opportunities or risks.
With that in mind, it is important to establish a strong presence in the company with a data team, showing clear proof of value and the opportunities for ROI, if proper support and sponsorship is given to the project and team. Minimally, when working with an outside firm to endeavor data projects, data stewards should be left behind to maintain and ensure the integrity of the systems put in place. A data model is like a new puppy in a bathroom, the puppy is clean and the bathroom is neat when you set up the scenario but once you close the door and the puppy is left to its devices with no guidance or oversight, you will come back to a spectacle of toilet paper, poop, pee, and who knows what else. There is an old saying, garbage in, garbage out but the truth is garbage shouldn’t make it in if you have key individuals overseeing the system and the tools properly programmed to govern the model and policies.
Now that you have taken the time to understand how to bring your data together into a single view let’s talk about the value this can bring your organization. The most important and first realized benefit is the efficiency it gives your system users from the top down in accessing the information. With dashboards you can generate clear information and reports to demonstrate any KPI’s or other key data points for quick summary to business leaders. With drill down reporting you can generate data reports for users to take action on across the organization. Unlike, BI (business intelligence) tools that work with large data sets and drill down reporting, you can take action in an advanced MDM tool where you cannot in most big data tools on the market, because the data dumps there it does not communicate in an ecosystem of integrated data.
The new unified data set and integrated ability to manage it all gives the owner the ability to evaluate and analyze the data to make strategic decisions. Evaluating the goals of your organization are crucial to ensuring you generate the correct reports and analysis. If your goal is to reduce cost and increase efficiencies, you should look at workflows that automate actions, reduce user level of effort, and identify key areas where data can be reduced by merging key data and removing duplicates. This can create reduction in inventory, increased buying power with suppliers, efficient record management of customer or employee data, and many other follow-up actions based on these reports.
If you are looking for support to get started or a firm to support a full-scale project, contact RI Services today. We have experienced data scientists and project managers on staff to ensure an efficient and effective data architecture and model are implemented in a timely and efficient manner. Contact one of our data specialists today to get started.
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