Offerings - DataWorks 360

OVERVIEW

The DataWorks 360 Process

Customer Analytics developed a time-tested approach and process to tame and organize data so it becomes manageable and usable – be it for software systems, Business Intelligence or Analytics and Machine Learning or AI. This is DataWorks 360 from Customer Analytics.

DataWorks 360 is a combination of Data Processing Expertise (via data experts) and a Data Processing Engine that can be tailored to your specific needs. This offering has two components:

DataWorks 360 - Discovery and Design

DataWorks 360 - Implementation and Delivery

Data Discovery Survey
We collaborate with our client’s business and IT teams to capture foundational information about data goals and the current data landscape, using the DataWorks 360 Discovery Survey Tool.
Implementation and Delivery
This process includes infrastructure setup (CA-hosted or client’s infrastructure), assigning a team with the right skills, and setting up and operationalizing the process. While delivering this component of DataWorks 360, Customer Analytics provides a stream of output. Data testing and data validation are part of the delivery.

Process Intelligence

Get visibility into your Data Processing

An additional part of DataWorks 360 is the Process Intelligence layer, which provides visibility into the progress of data through multiple processing steps such as source data profiling, data injection, cleansing, loading, curation, etc. It has intelligence to detect anomalies in source data, other irregularities and proactively alert the user so that data discrepancies do not impact downstream systems.

Key Features

With Process Intelligence, you can:

1
Track data progress across multiple stages from source to reporting layer.
2
Monitor real-time performance with metrics on processed vs. failed records, errors, and suggestions.
3
Get actionable insights and suggestions to improve data processes and reduce future bottlenecks.
4
Access comprehensive error breakdowns by stage to identify and address issues quickly.
5
Compare historical data to spot trends and make informed decisions for continuous improvement.