Azure Data Pipelines: 10-days Implementation

Emumba, US

Enable Azure Data Platform’s managed analytics services for your data in just 10 days.

In our digitized world, both data and data sources are growing exponentially. We know that data is gold; however, driving business value from these is a struggle for most companies. This struggle arises from several aspects: the canonical variability, velocity, and volume of Big Data; but also the inability to provision and maintain the infrastructure required to ingest, manipulate, and visualize this “Big Data”.

What if we can get your data into the Azure Data Platform’s managed analytic services in just 10 days? Once the data is available to use the might of lightning-fast analytic engines like Azure Synapse or Cosmos DB, you can quickly derive valuable insights.

In this service, we will use our expertise in Azure Data Pipelines to identify a single dataset that can be batch ingested, transformed and stored in an enterprise-quality data analytics platform that allows you to perform analytics, build predictive AI/ML algorithms and use them to make better business decisions --- all at the scalable cost model that is intrinsic to Azure Data Platform.


The engagement will be divided into 3 phases, spanning over a period of 10 days.

Phase 1: Discovery & Goals

In this phase, our business and technical experts will engage with you to understand your business pain points, explore available organizational data, and how it can be leveraged to give you the insights you are seeking.

Phase 2: Assessment

In the next phase, our Solution Architects will work on curating a customized solution that will convert your raw organizational data into useful technical and business insights.
Deliverable: Technical Proposal

Phase 3: Design & Deployment

In the last phase, our team of data scientists and engineers will ingest the data, curate the data, load it into your data warehouse or data lake, and create reports and dashboards to deliver insights.
Deliverables: Documentation of the infrastructure and data pipelines; Demonstration