Scalable and Clean Data Foundations
Jaimee Zipf
(NOTE: The name of the company and certain parts of the project have been changed to abide by NDAs)
Project Profile: Data Architecture and Governance Overhaul
Problem:
Strictly INTJ Solutions is struggling due to a lack of clear data framework and management, resulting in departments relying on outdated or inconsistent data sources. This has led to:
Misaligned strategies across departments.
Excessive spending on redundant data sources.
Duplicated efforts, with teams unaware of existing data solutions.
Non-compliance risks with global data privacy regulations due to insufficient oversight of data practices.
Objective:
The primary goal of the project is to design and implement a robust data architecture and enforce data hygiene practices to ensure:
Accurate, accessible, and high-quality data for all departments.
Executives can make data-driven decisions efficiently and effectively.
Compliance with global data privacy regulations is maintained.
Estimated Phases:
Assessment and Data Inventory
Conduct a comprehensive assessment of the current data landscape, including sources, systems, and usage.
Inventory all existing data assets and establish ownership for each dataset.
Data Architecture Redesign
Redesign the data architecture to ensure scalability, flexibility, and integration of data sources across departments.
Identify and eliminate redundant data sources to reduce costs and streamline operations.
Data Hygiene Standards Creation
Create a set of data hygiene and governance standards, including regular data audits, validation rules, and access control policies.
Ensure all departments adhere to these standards to maintain data quality and security.
Data Governance and Compliance Framework
Implement a governance framework that ensures alignment with global data privacy regulations (GDPR, CCPA, etc.).
Define clear roles and responsibilities for data oversight and compliance management.
Tool and Infrastructure Alignment
Assess and select the right tools and technologies for data management and analysis.
Implement data warehouses, ETL pipelines, and data governance platforms as needed to support the new architecture.
Training and Implementation
Conduct organization-wide training sessions to ensure all employees are aligned with the new data hygiene practices and governance standards.
Implement the new architecture and framework with a phased approach, ensuring minimal disruption to business operations.
ROI and Performance Evaluation
Measure the ROI of the new architecture and governance framework, focusing on improvements in data accessibility, quality, and compliance.
Regular performance evaluations to ensure continuous improvement and adaptation to new regulations.
Estimated Duration:
8 months
Key Milestones:
Assessment and Inventory (Month 1):
Complete the full assessment of the company’s current data sources and structures, including an inventory of all data assets.
Data Architecture Redesign (Month 2-3):
Redesign the architecture to streamline operations, reduce costs, and ensure easy access to high-quality data.
Data Hygiene and Governance Standards Creation (Month 4-5):
Establish formal data hygiene standards and implement governance policies for data accuracy, compliance, and ownership.
Data Governance and Compliance (Month 6):
Finalize and implement a compliance framework that aligns with international data privacy regulations.
ROI and Performance Evaluation (Month 8):
Conduct a thorough ROI assessment and evaluate the performance of the new data system, ensuring it meets strategic objectives and compliance requirements.
This project will enable the company to have a unified, efficient data management system, ensure regulatory compliance, and empower data-driven decision-making across all departments.
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Posted Sep 5, 2024
What is needed to correct data issues for a medium sized company without a solid data foundation? It may not be as complicated as you believe.
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