How_To_Drive_Analytics_Adoption_via_Data_Transformation

How to Accelerate BI Adoption on Snowflake

Have you spent long evenings and weekends building your data warehouse in Snowflake but are still struggling to get the rest of the organization to adopt it? Here is a sure way to get wider business adoption by getting the business teams involved.

Ebook Background

About this eBook

Building your data warehouse in Snowflake is a tremendous achievement but gaining adoption by the business is another thing altogether.  Data transformation has become an integral component to every modern data stack, alongside your cloud data warehouse such as Snowflake.  Data transformation also plays an indispensable role in the overall data lifecycle and analytics process, turning raw source data into valuable analytics data assets.

DataOps Process: How it helps

Data Transformation Workflow

The movement to cloud analytics and data warehouses has altered the overall data lifecycle and data transformation workflow

DataOps Process: Drivers and Objectives of DataOps

The Role of Collaboration

Collaboration is required to make the process extremely efficient and ensure the team is highly productive

DataOps Process: Data Platform Capabilities

Multi-persona Tools and Interfaces

The different personas involved in the data transformation workflow will have varying skills, technical expertise, and business knowledge

Search and Discovery

Rich faceted search capability, allowing users to easily search and drill down to potential assets they could use

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