Input Data

Owned by Mike Deskis
Last updated: Jul 01, 2024
5 min read

The PDR structure devotes a dedicated section to thoroughly defining the Input Data requirements for the proposed solution. This is a critically important component, as it meticulously outlines the specific data inputs that will be needed to power the core functionalities and essential capabilities of the envisioned solution.

At the heart of this input data requirements section is the need to clearly identify and map out the various internal and external data sources that will feed into the solution. This can encompass a diverse array of data inputs, ranging from enterprise business systems to third-party API integrations to direct user-provided data. The PDR must diligently document how data will be extracted, transformed, and seamlessly integrated from these disparate sources.

Beyond just cataloging the data sources, the input data requirements also delve deeply into specifying the different data types and formats that the solution must be able to ingest and process.

Equally critical is the assessment of the anticipated volume and velocity of the data. The PDR must carefully consider both the historical data sets as well as the real-time data inputs that the solution will need to handle.

Underpinning all of these input data requirements are the vital aspects of data quality, governance, security, and privacy. The PDR must outline the necessary data quality standards and validation rules to ensure the integrity and reliability of the data feeding the solution.

Purpose of Input Data Requirement

  • Identify and catalog data sources by document all the internal and external data sources that will feed into the proposed solution and map out how data will be extracted, transformed, and integrated from these diverse data sources.

  • Specify data types and formats to define the various data types (e.g., numerical, textual, date/time) that the solution must be able to ingest and process and outline the expected data formats.

  • Assess data volume and velocity to estimate the anticipated volume of both historical and real-time data that the solution must be able to handle.

  • Ensure data quality and governance to establish the necessary data quality standards and validation rules to maintain the integrity and reliability of the input data.

  • Enable Effective Solution Delivery using comprehensive input data requirements to ensure the proposed solution can effectively fulfill its intended capabilities by having the right data inputs.

Key Components of Input Data Requirement

Key aspects of the Input Data requirements in the PDR include:

Data Sources

The PDR identifies the various internal and external data sources that will feed into the solution, such as enterprise systems, third-party APIs, and customer/user inputs.
It clearly maps out how data will be extracted, transformed, and integrated from these different sources.

Data Types and Formats

The PDR specifies the different data types (e.g., numerical, textual, date/time, geospatial) that the solution must be able to ingest and process.
It also defines the expected data formats (e.g., CSV, JSON, XML) and any necessary data normalization or standardization requirements.

Data Volume and Velocity

The PDR assesses the anticipated volume of data (both in terms of historical data and real-time inputs) that the solution must be able to handle.
It also considers the velocity, or speed, at which data may need to be ingested, processed, and actioned by the solution.

Data Quality and Governance

The PDR outlines the data quality standards and validation rules that the solution must apply to ensure the integrity and reliability of the input data. It also defines the data governance policies and procedures, such as data ownership, access controls, and compliance requirements.

Data Security and Privacy

The PDR addresses any sensitive or confidential data that may be involved and the necessary security measures and controls to protect that data. It also considers the relevant data privacy regulations and the solution's alignment with those requirements.

KEY INSIGHT: Thoroughly defining the Input Data requirements, the PDR structure helps ensure that the proposed solution is equipped to handle the necessary data inputs, maintain data quality and integrity, and comply with relevant data-related policies and regulations.

Key Insights of Input Data Requirement

  • The PDR identifies the various internal and external data sources that will feed into the solution, such as enterprise systems, third-party APIs, and customer/user inputs.

  • The PDR specifies the different data types (e.g., numerical, textual, date/time, geospatial) that the solution must be able to ingest and process, as well as the expected data formats (e.g., CSV, JSON, XML) and any necessary data normalization or standardization requirements.

  • The PDR assesses the anticipated volume of data (both in terms of historical data and real-time inputs) that the solution must be able to handle, as well as the velocity, or speed, at which data may need to be ingested, processed, and actioned by the solution.

  • The PDR outlines the data quality standards and validation rules that the solution must apply to ensure the integrity and reliability of the input data, and defines the data governance policies and procedures, such as data ownership, access controls, and compliance requirements.

  • The PDR addresses any sensitive or confidential data that may be involved and the necessary security measures and controls to protect that data, as well as the relevant data privacy regulations and the solution's alignment with those requirements.

Key Takeaways of Input Data Requirement

The following are the key values and takeaways from role of input data requirements in the PDR:

Ensures the Proposed Solution Can Fulfill Its Intended Capabilities

The detailed definition of input data sources, types, formats, volumes, and velocities helps validate that the proposed solution will have access to all the necessary data inputs required to power its core functionalities.
This alignment between input data requirements and solution capabilities is critical for the solution to effectively deliver on its intended purpose.

Promotes Data Quality and Integrity

By outlining data quality standards, validation rules, and governance policies, the Input Data requirements help ensure the reliability, accuracy, and trustworthiness of the data feeding the solution. This data quality focus is essential for the solution to generate credible and dependable outputs.

Addresses Data Security and Privacy Concerns

The Input Data requirements section covers the identification of sensitive data and the implementation of appropriate security controls and privacy measures. This helps mitigate risks related to unauthorized access, data breaches, and compliance violations.

Facilitates Effective Data Management

The comprehensive definition of data sources, types, formats, and flows allows for better data management planning, integration, and orchestration. This supports the efficient ingestion, processing, and utilization of data by the solution.

Enables Scalability and Adaptability

The assessment of data volume and velocity requirements helps ensure the solution can handle increasing amounts of data and respond to evolving data needs over time. This scalability and adaptability is crucial as the solution's data requirements may change due to business growth, new use cases, or regulatory changes.