The data product lifecycle
Data products turn data into value. Once embedded in workflows, they help optimize operations, drive business decision-making, and enhance user experiences. Building data products is challenging. From design to deployment, here are the lifecycle stages that can guide data leaders.
Unlock the value of data products
From discovery to governance, learn the steps to building data products that drive business decisions and create value.
Unlocking value with data products
Data products, the tools, systems, or applications, turn data into value. Once embedded in workflows, data products help optimize operations, drive business decision-making, and enhance user experiences.
Chief data leaders advocate strongly for data products due to their role in driving value. Leadership agrees. In the most recent KPMG Data Products Survey, 90 percent of executives responded they are confident that data product investments will generate significant value. For more statistics and insights, download, “Unlocking value with data products.”
The challenge for chief data leaders is ensuring data products perform as advertised. That means every stage of development should be thoughtfully considered. Nothing trips up a data product faster than missing a stage or giving one short shrift.
The Data Product Lifecycle is shorthand for chief data leaders to ensure they cross Ts and dot Is during the development process. Follow these stages:
Define a data strategy
Chief data leaders should formulate a clear, coherent data strategy to guide development of data products that can also be articulated to leadership. Data profiling analyzes the fitness of data by uncovering its structure, relationships, and anomalies. Anything amiss can be addressed with data cleansing to improve quality. Strategy guides development while quality data powers outcomes.
Develop a framework
A framework stipulates how data is acquired and ingested. For example, data comes from various sources and transformed into a usable format in a data lake. The framework also specifies data modeling and quality assessment processes. Data modeling visually represents data, its relationships, and usage while assessments evaluate data for accuracy, completeness, and consistency.
Foster a data-driven culture
The chief data officer is both the data leader and a cheerleader. You initiate c-suite discussions around data’s value and importance, as well as promote data literacy among the workforce. Another job duty involves creating policies and procedures for data management. Empower even non-technical users to efficiently use data products.
Alignment with business objectives
Aligning data products with business goals is crucial for ensuring that products deliver value and drive business outcomes. This involves defining strategic impact objectives, managing risks, and continuously monitoring and improving data products through collaborative means. Co-sharing ownership of data products with other functions like IT and business functions help secure buy-in and success.
Building a data product that meets requirements
The building stage culminates the previous stages. Once data and tech dependencies are defined, data scientists do the groundwork of analyzing and developing models. A prototype is then built that validates the models and ensures it meets user needs. From there, the data product is embedded in workflows for monitoring and testing. Learning and improving never stops.
Testing to prove the value
Testing data products addresses the accuracy and reliability of results and measures user satisfaction. For chief data officers, testing allows for detecting performance drifts or data quality issues. Security testing is also critically important, ensuring data privacy and verifying users, as well as scanning for vulnerabilities. Set up alerts to quickly detect and address issues.
Governance
Governance is no longer a luxury; it is a necessity with data products. Governance helps ensure regulatory compliance, along with regular audits. Continuous monitoring verifies adherence to policies and procedures. Governance is being accountable to the goals set forth for data products but with a willingness to change based on new information.
Winning with data products
Chief Data Officers are in the spotlight with data products. They must quickly assess what needs to be done and then drive the process forward. Having the data product lifecycle to reference can empower you through strategic planning, cultural transformation, and operational excellence.
Download the paper below for a deeper dive on how to approach data products to ensure they deliver value to the organization.
Unlocking value with data products
Five steps data executives can take to build high-value data products and increase competitive advantage. Find out how by reading Unlocking Value with Data Products. Download and read the full report by completing the form below.
How KPMG can help
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Harness the power of data to modernize operations
By harnessing data, your business can produce data products, tools, systems, and applications that drive business decision-making and help modernize operations.
- KPMG named a “Leader” in Worldwide Data Modernization Services IDC MarketScape: Worldwide Data Modernization Services 2024 Vendor Assessment
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Make the difference
In an increasingly competitive landscape, harnessing the power of your data unlocks new business possibilities, decreases risk, improves efficiencies, and drives growth. However, to do so requires data that is relevant, accurate, and in compliance with applicable regulations. KPMG can help lead your data governance journey. We have the skills and tools to implement a framework that is guided by leading practices and tailored to your business needs.
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Matteo Colombo
Principal, KPMG Global Leader for Cloud, Data, AI , KPMG US
Danielle Beringer
Principal, Advisory, Lighthouse, KPMG US
Matteo Colombo
Principal, KPMG Global Leader for Cloud, Data, AI , KPMG US
Danielle Beringer
Principal, Advisory, Lighthouse, KPMG US