Uncover insights hiding in your data and analytic code
In two to four weeks, the Rapid Analytics Assessment will discover the hidden patterns affecting your current analytics performance, identify areas for process improvements, and provide you with a roadmap and strategy to deliver consistent analytics faster to your customers.
Increase analytic accuracy and reliability, removing revenue, cost and legal risks when analytics are operationalized.
Support advanced analytics and machine learning by uncovering analytic attributes and features across your data.
Find and isolate inefficient development patterns, variations or fluctuations in your KPIs, and training needs.
The first step is to collect SQL query history from your data platforms and the code from your SAS, R, Python and other analytic applications.
Our team will prepare the code and data and begin parsing SQL and unstructured text. From there, they’ll augment the dat set with additional features and write it all to files for analysis.
The team will then run eight analytic modules against the enriched files, build reporting and analysis tables, and then create visualizations with commentary.
In the final step, our team will deliver the findings to your team, put a roadmap together and provide you with immediate recommendations and actions you can take.
Our Account Managers are you go to resource for analytic assessment projects. They are responsible for the commercial relationship between you and Aginity.
Once we kick of a project, our Project Manager will work with your team to develop the project scope, communication and resource plans for the four weeks.
Your team will be assigned an Enterprise Analytics Consultant who will run analytic models, facilitate workshops, and develop outcomes and recommendations for your assessment.
Working closely with your team, the Data Engineer will be responsible for collecting, ingesting, and curating the engineered data set for the EAC to mine and analyze.
Before our crew comes in to deliver the Rapid Analytics Assessment there are a few things you will want to think about and prepare ahead of time. If you need help these just contact us and we will guide you in the right direction.
The assessment can be done at any time, but it will be particularly effective if your enterprise is facing any of the following situations.
Start with a clean slate—mitigate the risk of migration and make sure you’re only moving what needs to be moved.
This isn’t a people problem—it’s a productivity problem—and the assessment will uncover how much time is being wasted on redundant activity.
The assessment gives you a picture of what’s really going on with your analytics—earn some quick wins by improving consistency and productivity without additional investments.
Consistency and traceability offer safety, and the assessment will point out where you might be facing risk.
In recent years, a large international bank delivered $1 billion+ net revenue gains from their analytic efforts, helping them to jump forward in market position. This success also uncovered a challenge for them to continue to scale at this pace–it was driven by a manual operational processes–which meant higher business risks due to duplicative work and inconsistencies in the analytics driving business decisions across the organization.
“ Working together with Aginity, we found approximately 60-70% of the work across three teams was the same and resulted in different analytic results.”
Active Analytic Governance: Each calculation, metric, KPI, or attribute is now built once, changed only by an approved process, and every end-user uses the enterprise-approved definitions.
Active Business Continuity: Previously, if a calculation changed, the team had to find all of the places where that calculation was coded and make updates. Using Aginity, a single change updates all downstream dependencies and applications.
Feature Store to Drive Machine Learning: Data Scientists now leverage a consistent set of variables to quickly train models for faster iteration, innovation, and implementation.
A major grocery retailer’s data was siloed in 28 separate divisions-with 1,000+ unmanaged and inconsistent customer attributes-they lacked a unified cross-brand, cross-channel view of opportunities and their data analysts struggled to find and reuse analytics.
After the Rapid Analytics Assessment, the retailer formulated a new approach to analytics. With a new roadmap in hand and immediate recommendations to take action they reduced the time to launch a typical marketing campaign from 3+days to 4 hours.
“ Our business units measure campaign lift to optimize marketing spend. With Aginity, we uncovered we had 35 ways to define coupons. No wonder it was taking so long to measure performance and launch a new campaign.”