Create a well-defined foundation that streamlines the processes of connecting data sources and extracting insights
Use Case
Enterprise Data Consolidation
Enterprises that store their data in multiple places cannot consistently extract that data and mine it for insights. The results are duplicated effort and inconsistent findings. Consolidating to a single repository ensures consistency and accuracy for all users who base their decisions on data.
Bottom-Line Returns
Risk Reduction
Eliminate discrepancies from departments extracting the same data in different ways
Workforce Upskilling
Help your end users discover and share insights, instead of wasting time redoing work or questioning results
Business Problem
As enterprises make decisions on data from different sources, such as customer analytics, marketing campaign results and sales pipelines, they must connect and blend that data for a full picture. But when different users apply different methods to consolidate the same data, discrepancies arise. That can lead to different departments misunderstanding customer signals, inaccurately reporting financial results or reaching different conclusions on key performance indicators (KPIs).
Alteryx Solution
With an automated process that cleans and unifies all company data into a single repository, users are assured that they’re all looking at the same data. They can then apply the same business rules to make calculations like KPIs and pipeline status.
The main benefits of creating and enforcing a single data source are:
- Data Governance – Enforce calculation rules before data is extracted, reducing the time needed to arrive at results and ensure everyone is working from the same data
- Transparency – State which calculations are used at every point throughout the workflow
- Efficiency – Enable users to find and extract their own data, thereby reducing the burden on data science and analytics teams
With Alteryx, you can:
- Create a Designer workflow that connects to multiple data sources like Snowflake, Salesforce and MongoDB, and maintain it with Data Connection Manager (DCM)
- Create a transparent process that blends data and applies business rules automatically
- Schedule an extract-transform-load (ETL) process that runs hourly to populate, consolidate and update your data repository
Data Sources Simplified Workflow
1 – Data Connection
Use an Alteryx Data Connector to automate extraction from sources like MongoDB, Salesforce and Box
2 – In-Database Capabilities
Perform data prep and blend with the In-Database toolkit before extraction
3 – Prep and Blend
Easily combine data from all sources into a single data pipeline and automate application of business rules like KPI calculations
4 – Update Scheduling
Schedule your workflow to populate and update your data repository using Alteryx Server
Recommended Resources
Whitepaper
Building Data Talent for the Decade Ahead
This paper lays out several approaches that educational institutions can take to embed data analytics into legacy academic programs or the DIY path individuals can follow.
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