What Data Builders can do with Holistics

If you are a data analyst, data engineer or data leader, you are data builders who can make full use of Holistics’s functions and abilities. In Holistics, data builders’ can be assigned Admin and Analyst roles. Here are what data builders can achieve with Holistics:

Consolidate data from multiple sources

consolidate data

Holistics lets you unify and model your data from different sources, using SQL-based data models to generate analytics. You can just directly pull data from various data sources, such as CSV, Google Analytics, Google Spreadsheet or production data, etc. into your SQL database to start analyzing.

Map business logic to data logic

data model

With Holistics’s Data Modeling layer, you can map business logic to your physical data so the end-users can understand and explore data easily with minimal help from the data team. This can help reducing data miscommunications by offering a single source of truth for everyone to understand all different data definitions, from what a metric means in the business context to how it’s being calculated.

Transform your data

transform data

Data builders can build reusable data components from the imported raw data, perform complex data cleaning and standardize them with the Transform Model. Every transformation in Holistics is run against your Data Warehouse, so you can leverage both its storage and processing power.

Manage your data pipeline

manage data

Holistics provides a simple approach to help you automate and maintain the company’s full data pipeline and data sources without needing to trouble data engineers. You can maintain a scaleable data workflow with a unified and high-level view of your organization’s data.

Enable non-technical users to do their own analysis


No longer dread the constant stream of simple data pull requests nor bombarded by business users for ad-hoc analytics. After producing clean and well-documented data models, you can combine them into Datasets and that allows self-service analytics for business users.

This leads to a win-win situation: data consumers do not have to wait for you all the time, while you have more time to do analytics projects that deliver higher values to the organization.