Managed Analytics
What is you data telling you.
Overview
Analytics is a wide topic. It can cover everything from data analysis to machine learning and everything in between. It is heavily reliant on Data Quality to ensure everything is correct. Unfortunately, many organizations rush into it without first prioritizing good data. If you don't have good data yet, do that first. Then go do analytics.
Key Concepts
The most important attributes of analytics.
Quality Data
High quality data is a must for analytics to actually work. If your organization still have messy data, fix that first. Otherwise you are running reports that are incorrect.
Standardized Definitions
Standardized data is important in doing analytics correctly. When accounting and marketing use different things for the same thing it leads to confusion. You need standardized definitions across the organization.
Data Warehouse
If you want to do analytics seriously you want a data warehouse. It is a database specifically designed for analytics that is filled with data from production systems, using a data pipeline. It prevents running reporting on production systems that slows those systems down.
Dashboards
Dashboards are a great way to convey lots of information quickly and get a cohesive view of the business. They can have the metrics that are important to your business, add interactivity and update automatically.
Understand The Customer
Understand your customers through data analysis or machine learning. Who is likely to churn, create customer segments, offer recommendations and make predictions about future values.
Automated Reporting
Want to your leaders to receive daily reports in their inbox? No problem. I have created reports delivered in a variety of ways in a variety of formats.