Scalable Data Platform Research Center

Featured Research

Build a Scalable Data Platform Research Center Capstone

Building a data platform is a large and expensive undertaking. It is a long-term investment that requires a solid understanding of business data needs and careful planning to get right. Making the wrong decision has stalled many data initiatives, with platform cost shock and inability to meet business contributing heavily to short CDAO tenure. Info-Tech's aim is to assist in avoiding those issues and to help our members make the right decisions when choosing their data platform.

Scalable Data Platform Thought Model. Build with scalability, flexibility, security, and your budget in mind

Value of Data

Define Your Platform’s Foundations

A data platform is a supporting part of a complex ecosystem of data practices and capabilities. To become a data-driven organization that maximizes value from data, both your own and data provided by third parties, you must understand these disciplines, how they connect, and the tools and platforms that underpin them. Leverage these resources to contextualize this complex environment and build a data practice and platform to support it.

Data and Analytics Landscape Research Center Build Your Data Practice and Platform

Establishing the Value Case for Your Data Platform

The specific value cases that support the investment necessary for your data platform will be shaped by your data strategy as well as your requirements for how you govern and manage data to execute that strategy and how you establish data as a corporate competency. Leverage our key research in these areas to help justify investment in your data platform and demonstrate the business value it will drive.

Build a Robust and Comprehensive Data Strategy Establish Data Governance Foster Data-Driven Culture with Data Literacy

Progression & Management of Data

Plan for Data Growth, Scalability & Flexibility

The aggregation of your various use and value cases for data will shape the overall structure of your data platform. Individual use cases will define the requirements for how your platform must manage various pipelines of data from creation to delivery to consumption. The volume of data and the speed at which it must flow, in aggregate, will shape how your platform must flex and scale.

Data Platform Requirements

Leverage these resources to help map out the current and future data complexity you’ll need to consider when selecting your data platform, including determining the architectural patterns your data platform must adopt, the various types and speed of data integration it will need to support, and the data pipelines you’ll need to construct.

Build a Scalable Data Platform – Research Center Capstone Select Your Data Platform Build a Data Architecture Roadmap Build a Data Pipeline for Reporting and Analytics Build a Data Integration Strategy

Data Lifecycle Management

Your data platform will also need to support additional functionality for ensuring full and complete end-to-end data lifecycle management. Leverage these resources to understand the key practices most modern data platforms must incorporate to support effective data management and governance from creation to retirement.

Build Your Data Quality Program Develop a Master Data Management Practice and Platform Create and Manage Enterprise Data Models

Technology Enablement for the Platform

Select the Right Tools for Your Data Platform

Leverage our software reviews across the four phases of the data lifecycle to help you ensure you have the right tools to meet your specific data needs.

Data Creation & Ingestion

Data Integration (DI) Enterprise Service Bus (ESB)

Data Engineering & Lifecycle

Data Quality (DQ) Master Data Management (MDM) Metadata Management

Data Persistence

Analytical Data Store Transaction Data Store (TDS)

Data Delivery & Consumption

Data Preparation for Analytics Business Intelligence & Analytics (BI) Machine Learning Platforms (ML)