Gartner Research

Solution Path for Implementing a Comprehensive Architecture for Data and Analytics Strategies

Published: 28 June 2018

ID: G00351281

Analyst(s): Carlton Sapp


New analytic requirements need a flexible architecture for interoperating with diverse data sources and complementary analytic solutions. Technical professionals can use this step-by-step methodology to create a comprehensive architecture to support a data and analytics strategy.

Table Of Contents

Problem Statement

Solution Path Diagram

Solution Path

  • Step 1: Enterprise Information Management
    • 1.1 Information Governance
    • 1.2 Master Data Management
    • 1.3 Enterprise Metadata Management
    • 1.4 Data Quality Assurance
    • 1.5 Information Life Cycle Management
    • 1.6 Privacy and Security
    • What to Consider Before Moving to the Next Step
  • Step 2: Acquire and Organize
    • 2.1 Ingest and Analyze
    • 2.2 Process and Transform
    • 2.3 Integrate and Store
    • What to Consider Before Moving to the Next Step
  • Step 3: Enable Data for Analytics
    • 3.1 Data Warehouse
    • 3.2 Data Lake
    • 3.3 Data Virtualization
    • 3.4 Logical Data Warehouse
    • What to Consider Before Moving to the Next Step
  • Step 4: Enable Business Insights
    • 4.1 Business Intelligence and Visualization
    • 4.2 Self-Service Data Preparation and Analytics
    • 4.3 Advanced Analytics
    • What to Consider Before Moving to the Next Step
  • Step 5: Extend and Automate With Artificial Intelligence and Machine Learning
    • 5.1 Real-Time Analytics
    • 5.2 Machine Learning
    • Architect for Machine Learning
    • Leveraging Artificial Intelligence and Machine Learning API Services to Complement Your Data and Analytics Architecture
    • Accelerate Delivery of AI Technologies With Machine Learning as a Service and/or Embedded AI Services
    • Get Started With Accelerating Delivery of AI Technologies by Focusing on These Drivers
    • 5.3 Automate and Scale
  • Step 6: Deploy and Integrate Analytics Into Operations
    • 6.1 Analytic Deployment Architectures
    • 6.2 Points of Integration for Existing Analytic Systems
    • 6.3 Model Deployment for Data Scientists
  • Iterate for Continuous Improvement
    • Align With Business Strategy
    • Governance
    • People and Skills
    • Account for Citizen Roles
    • Agile Database Development
    • Cloud Versus On-Premises

Gartner Recommended Reading

©2021 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. This publication may not be reproduced or distributed in any form without Gartner’s prior written permission. It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact. While the information contained in this publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner research may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. Your access and use of this publication are governed by Gartner’s Usage Policy. Gartner prides itself on its reputation for independence and objectivity. Its research is produced independently by its research organization without input or influence from any third party. For further information, see Guiding Principles on Independence and Objectivity.

Already have a Gartner Account?

Become a client

Learn how to access this content as a Gartner client.