Mindtree helps organizations accelerate the journey from Data Engineering to Data Science using Azure Databricks.
The hardest part of building an intelligent enterprise isn’t AI, it’s Data. This is because the surrounding data infrastructure for data preparation is vast and complex because of which preparation and aggregation of large datasets becomes a major challenge. As a result, both data engineers and data scientists end up spending a lot of time to bring AI projects to life. Mindtree helps organizations use the power of Azure Databricks which is an Apache Spark based unified analytics and collaborative platform to engineer data and generate productive insights.
We support organizations across the following use cases for adopting Azure Databricks:
a. Building a new data ecosystem: For those who lack a significant data infrastructure and rely on basic reporting and spreadsheets for insight.
b. Migrating from Spark to Databricks: For those who are using Apache Spark today on Hadoop or Cloud and looking to improve performance of Spark by using Azure Databricks.
c. Modernizing the data ecosystem with Spark: For those having a legacy and complex big data infrastructure which hampers data engineering and science.