Self-Service Data Interfaces
By: Viji R
Tags: Big Data, Data Visualization, Data Science, Capital One

In today’s world, technology is analogous to data. Netflix, Uber, and LinkedIn are pertinent examples of firms that have tapped into the symbiotic relationship between data and technology. Firms such as these increasingly rely on data to make strategic decisions ranging from hiring to budget allocations to managing day to day operations. Every customer touchpoint is digitized and recorded for analytics. Similarly, Capital One, a pioneer in information-based decision making, has invested heavily on accumulating large amounts of data in order to inform multiple aspects of its business.

However, data that is not used effectively is as good as data that does not exist. For example, a line of business within an organization may invest analyst time on gathering data from its enterprise data warehouse, performing a data analysis to address a business problem. This work and the outcome of the analysis often remains within the confines of that business line. More often than not, another business line within company may want to perform the same analysis; but in the absence of an information wiki/knowledge repository, they have to start from scratch, causing the same work to be repeated multiple times.

If commonly used analytical data is consolidated, processed, and presented via a standardized presentation layer with search functionality, the repetitive and redundant work is significantly reduced. Organizations often focus heavily on streamlining and centralizing accumulation and storage of data. Often a much lower investment is made into presentation and delivery. To really tap into the power of analytics, the data/tools used in a project need to be matured by creating efficient presentation/consumption layers that not only serve as a visual representation of information for its immediate users, but also acts as a self-servicing layer for the broader enterprise community.

The Three Levels of Presenting Data for Consumption

Traditionally, data is presented for consumption in three ways:

1. The basic level is the actual raw data that can be used as-is and is in the most granular form. This is useful for analysts and developers looking for more flexibility to massage the data to their needs. 2. The second level of presentation involves applying some refinement to the data so it can be used in repeatable processes such as standard reports. 3. Finally, the highest level of presentation is visualizations and business intelligence which involves presenting data visually to generate business insights.

An efficient and well-designed presentation layer has to address all three needs. Hence, a digitally-driven organization has to consider the implications of all three levels of data presentation and their consumption requirements.

Investing in Solutions to Reduce Complexity

Digitization requires reasonable investments in the Cloud and enterprise technological capabilities. These technology investments can vary from data centers to Platform as a Service models to databases to software to tools etc. The behind the scenes cost data on these investments is often complex, segregated, and confined within individual lines of business. For as these investments grow, each line of business will need to maintain complex technology cost structures and a footprint spread across both their on-premises and Cloud platforms. An integrated enterprise-level technology cost data warehouse with standardized analytical frameworks and presentation layers can create tremendous value for leaders to understand and benchmark their costs.

One such effort within Capital One is the Tech Cost Transformation. The goal of this initiative is to consolidate and streamline the collection, storage, and presentation of technology costs data while creating standardized analytical capabilities to enable transparent and efficient cost management. A repository of cost enriched data has been gathered from individual line of business data sources and a financial management tool scores the cost models to process the data and the associated financials. In order to make such large volumes of processed data from disparate sources available for usage, this web-interface was designed to create a standardized presentation layer addressing all three data consumption needs stated above.

Delivering on Data Presentation Needs

A data presentation layer built as a web-interface can facilitate easy access to data and program information. Hence the content flows on the website are designed based on the evolution of the cost transformation program. The application is hosted in our Cloud environment and creates the required user layers to easily get to our standard Reporting and Data Suites. Each page has been designed to serve as an information wiki to the data.

We recognize that not everyone who needs access to this data is an analyst or technologist; so the pages are created to convey the program story to a broader, less specialized audience. Users familiar with the program can navigate to interactive reports and the downloadable data files. Alternately, someone new to the program may simply browse the self-service pages to obtain contextual information before engaging with the data.

Our overall aim is to create self-servicing capabilities to meet the needs of all audiences with diverse skill-sets and unique data needs. This style of presentation layer was our solution to making data access simple and effective. Data delivery and presentation are as important as streamlining & centralizing accumulation and storage of data. Our belief is that accessible self-servicing data layers can build excitement and increased activity on your data.

Conclusion

In a nutshell, collecting data is only the first step in the process of working data into your business plan. Creating service layers for data presentation can create extensive usability. Extensive usability can lead to better analysis. Better analysis can lead to better decisions. Better decisions can enable increased organizational success. Here at Capital One we’re dedicated to maximizing every layer of our data on our journey.