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Don’t Skip the Data Staging Step

Aug  24 
Terry O'Donnell  Director, Professional Services, Fiserv 

Proper data staging drives higher ROI on analytics

We’ve all seen a knowledgeable chef sort through an array of raw ingredients, combine those that work well together, and cook a delicious meal.

Like cooking, data staging can be seen as an art form that leverages industry knowledge, creativity and the anticipation of expectations. Data staging enhances the raw data by consolidating key elements into fewer objects that include relationships with other data sets, prebuilt calculations, classifications and hierarchies. It ultimately makes the data more user friendly for information workers to interact with, filter, sort, drill, summarize, trend, visualize and mine for insights.  

Data staging is best performed by a data steward who anticipates how the data will be presented and consumed. Financial institutions can maximize analytics with a data steward who is fully focused on presenting actionable information that aligns with the financial institution’s data plans and business strategies.

Unfortunately, many financial institutions put this preparatory work on information workers and their reporting software – like asking the customer to prepare the meal. The information worker spends more time collecting and trying to organize the data than analyzing the data, resulting in disorganized reports and visualizations along with data-access bottlenecks.

Having a data steward governing and packaging the data for self-service access ensures that the information is accurate, meaningful and available.

Align With Business Objectives

Executives, lines of business owners and data users generally interact with dashboards, which present data in a summarized fashion using visualizations and crosstabs (also called pivots). Dashboards typically aggregate data across various dimensions and timeframes so visualizations need to be organized in a way that communicate the message of what is happening and what the data is telling you.

Data staging is critical for the following reasons:

  • Unlocks the value of your data to a much broader audience
  • Typically improves performance
  • Preps data in formats required to create dashboards and visualizations
  • Takes the burden off data users, who aren’t highly versed in technical functions that are needed to prepare the data
  • Provides a governance layer to ensure data is accurate

The data steward concentrates on capturing organization-specific data and metrics, combining it with relevant system data, and then creating reports and dashboards that align with the organization’s business strategy. Having a data steward governing and packaging the data for self-service access ensures that the information is accurate, meaningful and available.

Typical staging tasks:

  • Import external data
  • Combine data into views that include key dimensions from various datasets
  • Combine data from different time periods that include historical perspectives to facilitate trending
  • Perform code translations to legible literal descriptions
  • Build classification descriptions to group detailed categories into more summarize groupings
  • Breakdown dates into components like year, quarter, month, week

Analytics Quality Impacts ROI

High-performing financial institutions embed analytics into everyday processes and goals by aligning reports and dashboards to business objectives. No surprise that higher performing departments or branches use dashboards while lower performing departments or branches do not. When people are focused on the right objectives, the whole organization benefits.

When data is prepped, enhanced with meaningful business logic and vetted, data consumers can make better informed decisions affecting strategic and business objectives across multiple levels. 

Sustaining a data-driven organization requires ongoing planning, execution, measurements and adjustments. If your data strategy is new, developing or mature, Fiserv professional services are a valuable resource you can engage to help develop your data approach.