Azure Data Engineering Implementation: 6-Wk Implementation

Are you:

• Struggling to know the best methods of extracting, transforming, and loading your data?
• Wondering how to establish an efficient data model with all your data sources?
• Searching for the optimum automated processes for collecting your data, cleaning your data, and adding it to your data warehouse?

When you first start your data journey you are faced with several raw data sources and many KPIs to derive from those sources. The biggest problem you will tend to face is how to collect all this data and form a structured and effective data model from it. This is where data flow and ETL processes come in, with an efficient data engineering process you can automatically pick up this raw data, clean it, transform it, and combine it to make an interlinked data model that you can easily find key metrics from. At Jarmany we have done this many times, and we know exactly what process you need for your data. We can offer expert advice on setting up Azure data ingestion and data transformation processes. Having worked with Azure Data Factory and Azure Databricks on many occasions we can help you set up a Data Factory pipeline that connects to your data through multiple connectors, whether it’s from an API, from a File System or in an Excel spreadsheet, Data Factory can connect to it. Then through a variety of activities within Data Factory we can move your data, clean it, and store it.

Deliverables:

• Initial review of your current data engineering process
• Give our recommendations of the best services to solve your data processing problem
• Create the services and data flow pipelines to collect your data, clean it and transform it
• Evaluate the solution and teach you how to maintain them, so you can handle your own data engineering structure going forward

About Jarmany: As a Microsoft Gold Partner with many Microsoft Certified Data Engineers who have created dozens of processes for a variety of clients using a variety of data sources, we know exactly how to formulate the best data engineering process for you. From vast amounts of messy web scrapping data to digital retail sales data we know what service will suit your needs.

*The cost can vary depending on the scope/scale of the use cases and services selected and number of use cases selected to investigate.