Customer Situation – A strategic direction towards moving IT infrastructure to the Azure Cloud was embarked upon after a detailed and holistic business analysis. Their data integration platform was one of the early candidates for migration.
Refactored iWay integration server data pipelines to Azure Data Factory, specifically:
Migrated iWay packages to SSIS run time in Azure Data Factory.
Leveraged Data Migration Assistant to deliver performance and reliability improvements in schema, data, and uncontained objects from the source to the target server.
Products and Services
Azure Data Factory
SQL Managed Instance
Compute characteristics of the workload matched in the infrastructure for better economics.
Migration to platform services enabled lowered operational costs from negating server management and built in business continuity.
Customer Situation – The legacy analytics platform build on Oracle database and data engineering products was due for modernization because it was unable to meet the business intelligence demands of the organization – from both a scale and turnaround perspective.
DSI provisioned an Azure Data Lake to ingest, prepare, transform, enrich, and curate data made available by source systems data providers via Rest API end points.
These data were then warehoused in Azure SQL Managed Instance (SQLMI) in a format conducive to data consumption and virtualization.
Products and Services
Azure Data Lake
Azure SQL Managed Instance
Reduced data duplication and simplified integration for improved data quality and near real-time reporting. This was critical to manage inventory levels.
Enabled self-service information access via more user friendly and business centric table schemas.
With over 1,700 acres of premium vineyards and 140+ years of industry experience, our client chose to migrate from a legacy Oracle Enterprise Data Warehouse platform to a modern data warehouse architecture, built on the Microsoft Azure Data Platform to provide enhanced performance and functionality in support of their analytics needs.
As a long-time business partner, DSI’s experience with the Microsoft Data Platform and building analytical solutions with Canadian liquor board data provided us with the knowledge and understanding required, to play a leadership role in transforming our client’s analytics solution.
An enterprise data lake, utilizing Azure Data Lake Storage.
A modern data warehouse platform, employing Azure SQL Data Warehouse to curate cleansed data in a conformed dimensional model.
Azure Data Factory Extract, Load & Transformation (ELT) processes, to manipulate data from various sources, move this within zones in the data lake and load this into the Azure SQL Data Warehouse.
Azure Functions, for file pre-processing.
Azure Analysis Services providing common and performant data sources, for multiple end-users to interact with uniform business logic, measures & attributes in a semantic layer.
Power BI to enable intuitive end-user interaction with the data available.
Azure Automation, for platform scheduling.
Azure KeyVault as a secure secrets store.
Azure Active Directory, for identity management and application access management.
Azure Security Center providing centralized visibility of the security state of components.
Log Analytics collecting telemetry and other data, providing a query language and analytics engine that enables insights into the operation of applications and resources.
Consolidation of the client’s BI and Data Warehousing capabilities into a single solution stack in Azure.
A re-design and enhancement of the platform, to increase and improve available features and ensure a highly supportable and performant solution.
The provision of value-add to business users, by incorporating refined and enhanced organizational functional & non-functional requirements.
A legacy of comprehensive documentation of the solution and how to operate it.
With over 70 years of industry experience in the insurance and financial sector, our client decided it was time to move to an analytics solution that would provide them with greater scalability, more predictable response times, and enhanced extensibility they needed to grow in the future.
With computing power highly utilized in the on-premises Netezza appliance leading to unpredictable response times, and with available storage space rapidly being consumed rather than continuing to invest in the legacy on-premises appliance, DSI enabled the migration from the existing on-premises Netezza implementation to Azure Synapse SQL Analytics by leveraging our technical expertise and delivery methodology.
Our practices are designed to deliver business value, taking into consideration the technical and business attributes of a given environment. We use Agile practices developing and delivering incrementally and iteratively with the emphasis on continuous analysis, monitoring, and improvements throughout the project phases, as well as Waterfall and Hybrid methodologies with heavy up-front planning and design before we kick off the project execution.
Azure Synapse Analytics dedicated SQL pool.
Attunity Data Replication.
Created a process that allows our client to spin up new Azure Synapse environments and populate them.
Automated regression testing strategies, to ensure that any ETL process is correctly migrated.
Configuration of any operational support objects, to support Azure Synapse and DevOps.
Migration of all objects, data, and workloads from Netezza to Azure Synapse.
Migration of all stored procedures from Netezza to Azure Synapse and testing against results in Netezza.
Assistance and support with production and non-production environment deployment from scripts, the connection of CDC, Informatica, Java to staging tables, and connection of SAS, MicroStrategy, and Denodo to the Azure Synapse Instances.
Provided our client with a refined project plan, together with the setup & configuration of any agile development management tool required.
Replaced an aging Netezza storage appliance with Azure Synapse SQL Analytics (Azure Synapse).
Migrated and transformed the Extract, Transform and Load (ETL) stored procedures from Netezza SQL to the Distributed SQL supported by Azure Synapse.
Supported end-user migration of Netezza SQL.
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