But how do you know how to look at your data to find your most valuable customers and optimize your business to serve them well? After all, your customer data is full of possible connections, insights, and game-changing decision drivers, but typically, the way the data sets are organized can actually stand in your way. Most organizations’ data has evolved, over years or even decades, from a rich mix of structured and unstructured data sources, in various formats, so masses of valuable data exists…but using it well is another matter.

Data sources may not be adequate. Data capture is often inconsistent from one purchase point or platform to another. Some data sources may not contain all the types of information your analysts need to succeed. Data sources might come with gaps or ambiguities.

Data sources are often disconnected. Analysis is often based on subsets of your data or limited data sources. Sometimes this is an access problem. Your analysts find themselves only using easily accessed data, leaving valuable information on the table. Sometimes it’s a problem of joining disparate data sources in different formats.

Often, data analysis takes too long. Sometimes it’s simply an issue of size, that data sources are far too massive to be effectively combined without slowdowns. Sometimes it’s an issue of access, that critical data sets aren’t easy to get. This problem results in insights bubbling up too late; they would have been useful a week or a day ago, but now can’t be applied for best effect.

Overcoming these challenges begins with asking a set of questions.

1. Do you have all the data you want to understand your customer better?
2. Are there data sources that you can’t access?
3. What data is missing?
4. What columns couldn’t you live without?
5. Are some columns typically incorrect?
6. How often do you guess where the data might be?
7. How many customer records have all of the data that you need?

AtScale offers a streamlined way for organizations to create a rich, self-service semantic model, across first-party and third-party data sources. It’s used by Global 2000 companies to help them discover the most valuable characteristics of their most valuable customers.

AtScale serves as an engine that accelerates and deepens analysis. By providing a connection to all disparate data sources, including data lakes and data warehouses, it gives analysts an agile way to build new data models based on a broader set of data where new data sets can be added quickly. And by providing a “virtual cube” for any and all business intelligence tools, AI/ML tools, and applications, everyone is able to use the same data with consistent definitions for improved consistency without concerns about added complexity or reduced performance.