Building data pipelines

The dyson vacuum for Microsoft Azure Data Lake Storage migration

The Challenge + Our Solution 

While migrating to Microsoft Azure Data Lake Storage (ADLS) can provide many benefits, there are also several challenges that businesses may face during the migration process. Here are some of the key challenges that businesses may encounter when migrating to ADLS: 

Data Compatibility: One of the main challenges of migrating to ADLS is ensuring that your data is compatible with the new platform. ADLS supports a variety of file formats, including CSV, JSON, and Parquet, but if your data is in a format that is not supported, you may need to transform it before migrating it to ADLS. 

  • Incorta creates a digital twin of your operational sources, providing superior analytics experience for business users and data engineers to interact with and analyze the most accurate, and up-to-date data without limitations or delay. 
  • By storing data on Azure ADLS as compacted delta tables, Incorta enables seamless integration with other Azure tools for open data usage. Delta tables provide a versioned and transactional view of the data, allowing for efficient processing of large data sets. This integration with other Azure tools enables organizations to leverage the power of the Azure ecosystem for data analysis, business intelligence, and other data-driven initiatives. 

Data Security: Data security is a critical consideration when migrating to any new platform, and ADLS is no exception. Businesses must ensure that their data is properly secured during the migration process and after it is transferred to ADLS. 

  • Incorta’s fine-grained security can replicate application-level security to enable analytics on sensitive and private data. 
  • Additionally, Incorta provides a Delta Sharing client to ensure open cross-platform sharing, centralized governance, and easy collaboration all with the comfort of knowing data privacy is priority #1! 

Data Complexity: Moving large amounts of complex operational data to ADLS can be a time-consuming process. The complexity of logic from customized enterprise platforms can quickly uncover complexity that limits migration efforts due to technical or domain expertise. 

  • Incorta’s prebuilt templates accelerate users’ analytics and reduce data engineers overhead, while delivering frequently refreshed, trusted and secured data to your Lakehouse of choice. 

Data Volume: With the sheer volume of operational data, engineering teams quickly find themselves slicing, dicing, and aggregating data in pipelines to ultimately fit end-user requirements. We all know too well that requirements change. With that comes munging through legacy data pipelines and migration paths to pull source system data. 

  • The more granular the detail, the more Incorta differentiates itself from other technologies. Thanks to the ingestion process, Incorta preserves the data at full-fidelity and in third normal form (3NF). While this may sound counter-intuitive to many engineers, Incorta’s secret sauce lies in its ability to pre-calculate joins and traverse 3NF models without losing details to star schemas. 

Cost Management: While ADLS can be a cost-effective solution for storing large amounts of data, it’s important to understand the pricing model and how it will impact your organization’s budget. Businesses should consider factors such as storage costs, data transfer fees, and analytics costs when planning their migration to ADLS. 

  • With Incorta, organizations can implement analytics module-by-module, growing their investment incrementally as value is proven. Data is stored at a fraction of the cost of a traditional data warehouse Therefore, organizations benefit from reduced reliance on expensive data integration tools and ETL pipelines, helping streamline operations and further reducing costs. 

Performance: Migrating to ADLS can impact data performance if not done properly. Businesses should ensure that their data is properly optimized and configured to take advantage of ADLS’s performance benefits. 

  • Avoid the challenges associated with reshaping data using traditional ETL pipelines. Land full-resolution data in the cloud in a form that directly supports analytic queries and becomes productive instantly.   

A Successful Migration Story 

One of Incorta’s customers, an intergovernmental organization with many subsidiaries, was migrating from a legacy data warehouse in PeopleSoft to Oracle Cloud Fusion ERP with modules in HR, Finance, Procurement, PPM and Cloud solutions Salesforce and Service Now. This is a great migration for any organization that takes time, effort and many considerations.  

Their decision to leverage Incorta to connect these cloud applications and ingest the data with Direct Data Mapping and land the data into Microsoft ADLS was highly successful. The organization was then able to model the data correctly and rapidly into Microsoft Synapse for Power BI consumption.  

Their business users in Finance, HR, Project Management can now understand the SLAs with grants and donations and how funding is properly executed within these agencies. The CIO of this organization has dubbed Incorta “The Dyson Vacuum” because of its ability to pull data out of cloud applications and rapidly deliver to the Microsoft Cloud data warehouse and reporting solution. 


While migrating to ADLS can offer many benefits, it’s important for businesses to understand and address the challenges that may arise during the migration process. The use of Incorta combined with proper planning, testing, and execution can help ensure a successful migration and enable businesses to take advantage of ADLS’s scalability, cost-effectiveness, and security features.