Data warehouse modernization: a how-to guide
July 6, 2023
The role of data warehouse modernization
Research by BARC and TDWI highlights the most common reasons, approaches, and results of data warehouse modernization.
of organizations aim for greater capacity to scale data, users, and analyses
of respondents choose DWH automation as their main modernization approach
of companies modernizing their solution achieve broader data warehouse usage
Top 10 data warehouse modernization essentials
Before delving into specific use cases and strategies, let’s briefly review the general cornerstones of the DWH modernization process.
Ability to handle any type of data
including structured (i.e., financial transactions), semi-structured (emails), or unstructured (imagery).
Real-time data processing
to get actionable business insights from continuous data streams and enable operational business intelligence.
Compatibility with major data processing engines
available on the market, including Spark, Flink, Hadoop, Samza, and Storm.
Reliance on cloud technologies
to benefit from improved scalability, processing power, faster deployment, and managed infrastructure and security.
Support for various deployment models
including on-premises, multi-cloud, or hybrid cloud, and interoperability among multiple cloud environments.
to facilitate access to data for users with different roles and needs, including data scientists, data analysts, and report writers.
between the data warehouse and other data management platforms to create a unified ecosystem and minimize information silos or inconsistencies.
Automation of numerous tasks
such as data ingestion, transformation, and management to speed up analyses and improve accuracy.
Adoption of AI and machine learning (ML) algorithms
for automated data integration, cleansing, and stream processing.
Focus on compliance
by implementing cybersecurity features and data governance policies that ensure enterprise data assets are properly stored and shared.
10 data warehouse modernization use cases
An organization should consider data warehouse modernization when dealing with the following scenarios:
Scheme title: Top 10 leading drivers for data warehouse modernization
Data source: cloudera.com — The Modernization of the Data Warehouse
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Major data warehouse modernization strategies
Depending on your business priorities and requirements, there are different ways to approach data warehouse modernization.
Data warehouse automation
- Azure Data Factory
- Azure Synapse
- Microsoft SSIS
- Microsoft SQL Server
- AWS Glue
- AWS Step Functions
- Informatica’s Intelligent Data Management Cloud
- Oracle's Autonomous Data Warehouse
Scheme title: Automated ETL workflow through AWS solutions
Data source: aws.amazon.com — Orchestrate an ETL process using AWS Step Functions for Amazon Redshift
Top platforms for data warehouse modernization
The range of cloud-based solutions available on the market is rather extensive. Here are some popular options you may consider when modernizing your data warehouse.
Benefits of data warehouse modernization
Companies that modernize their data warehouse may expect to achieve the following pay-offs.
Modern data warehouses can efficiently handle large volumes of data and complex queries due to faster processing times.
Cloud-based DWHs can scale up or down depending on business needs without requiring additional hardware or infrastructure investments.
Organizations can mitigate infrastructure and maintenance costs by migrating to a cloud-based data warehouse managed by a service provider.
Modern DWHs offer real-time analytics capabilities, enabling faster report and analysis cycles and ongoing operational adjustments.
Wider data pool
A modern data warehouse supports many types of data and formats, allowing organizations to collect information from numerous sources.
Modern DWHs use data encryption and multi-factor authentication to protect sensitive data from unauthorized access.
Modern data warehouses improve cooperation across teams by providing a single source of truth and facilitating data sharing.
DWH automation can foster compliance by automatically performing data management and reporting tasks more accurately than humans.
Data warehouse modernization barriers and best practices
Data warehouse modernization often comes with several technical and business challenges. Here are some recommendations for overcoming issues:
Get started with DW modernization
The data tide unleashed by mass digitalization is paving the way for new, unexpected business opportunities. However, it's also putting a strain on data management and business intelligence ecosystems, including data warehouses that will require a radical overhaul by means of cloud technologies, automation, and operational BI. Having an experienced partner like Itransition will help you get the most out of your data warehouse modernization investment while overcoming potential challenges.
Leverage our solutions to seize value from your data
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