Sharing Our Passion for Technology
& continuous learning
〈  Back to Blog

Our Approach to Data: Bridging the Gap Between Development and Analytics

Three pairs of hands at a desk with ipad, calculator, keyboard, and papers

Data analytics unlocks the power of data to inform business decisions and streamline processes. Our forward-thinking approach combines development teams with analytics experts at the beginning of the software development lifecycle to make data analyzable from the start. This post is an excerpt from our latest Executive Overview: Analytics Synergy in the Modern Software Development Organization.


Decision makers in modern organizations need the ability to combine and analyze data from many systems in order to gain insights and drive business direction. Historically, this has been achieved by forming analytics teams responsible for transforming data from source systems into a central data store, on top of which they create reports and dashboards.

The problem with this traditional approach is that each additional data source comes online, and with each new question asked by the business, an additional burden is added to the analytics team. How does an organization embrace this growth?

A shared ownership strategy allows analytics to scale with the organization. This approach combines development teams with analytics experts early on in the application development/configuration process, making the data analyzable from the get-go. This realignment makes increased data attributes, sources, and granularity an asset rather than a burden on the business. It also reduces the time and cost of managing the current infrastructure, and it positions an organization to use data to be competitive in their market.


Many businesses are still using centralized data platforms, meaning the information is stored and maintained in one location (data warehouse or data lake) and often governed by a dedicated analytics team. These individuals are responsible for transforming data from source systems into a standardized model, often then building dashboards and reports on top of this warehouse. A drawback to this approach is that an organization-wide analytics project employing this strategy might spend a year’s worth of effort and resources before the first report is ever produced.

There’s also a high risk that a dedicated analytics team responsible for overseeing all the data will generate a bottleneck in business decision-making. As problems continue to arise, data analysts must balance a backlog of data integration work with existing systems and new requests to answer new questions.


Data analysts and development teams can opt to work together during the project’s inception to ensure that both groups understand the source systems inside out, as well as making sure the data is analyzable and easily interpreted.

  • Request that your application development teams expose their data as part of the initial app development (i.e., “shift left analytics”).
  • Empower application development teams to own the concept of making their data analyzable, thereby removing the bottleneck of a centralized organization.
  • Serve the analytics needs of today and tomorrow.
  • Iteratively build analytics solutions starting with the first initial report in parallel with the application that sources the data.
  • Have analytics specialists mentor and educate development teams in the use of data and tooling. Decentralize analytics to provide economies of scale, data permanence, etc.
  • Include analytics professionals on product teams without changing who team members report to. Business stakeholders overseeing the development of applications within the organization will need to expand their view to include making data analyzable, as they are the best equipped to understand the data their applications produce.

As business needs continue to evolve alongside technological innovation, the more traditional data models and centralized analytics expertise can no longer effectively serve large corporations. There’s a growing need for real-time data analytics, and businesses can’t afford to make faulty decisions based on bad data. Sharing distributed data and analytics responsibilities is a transformative solution that allows your business to answer the questions it needs today without impeding your ability to answer tomorrow’s questions.

To learn more about our approach, download our Executive Overview: Analytics Synergy in the Modern Software Development Organization.

〈  Back to Blog