How Sprinkle Empowers Different Teams

Here’s how Sprinkle helps various department within the enterprise and how it reverberates at different levels of the organization.

Enrich data and define metrics

Sprinkle is an ETL tool that provides top-notch flexibility in terms of user accessibility. The tool is hassle-free and could be easily used by the product and the business teams. Sprinkle’s self-served analytics and the ability to build reports on the go means it doesn’t require an in-house analyst to generate reports.

Basically, most ETL tools deal with high-level querying in order to build and generate reports. However, with Sprinkle, any user without any technical knowledge would be able to perform queries and generate reports with nominal IT support.

Most queries are auto-generated and they come handy for non-technical users as they have point and click interface. They are simplified and scaled-down for easy accessibility and the complexity in collaborating and sharing within groups are eliminated.

Data Science Team

With Sprinkle, data science teams can build intricate fact tables and models with the data. In order to analyze, build complex reports, and perform supervised learning, ML and AI holds the key. It is where datasets are provided and models are built to solve any particular issue using Machine Learning modules and algorithms.

With Sprinkle’s REST APIs, users can build powerful machine learning applications and algorithms in the platform of their choice. The ease in building a data pipeline is brought by AI and ML features inculcated in the tool.

Exploratory data analysis can be performed using Sprinkle libraries in Notebooks. Data models and fact tables can be created in a way where users can predictively test, discover and strategize their business. It can be done using any popular data science applications and tools like Python, R, PySpark, etc

Data Analysts

Sprinkle is capable of integrating data from any source platforms, combines datasets, and provides simplified analysis. The tool works on top of all leading open-source platforms hence it keeps up with updating schemas and APIs to provide precise analytics and perform ML and AI operations.

As the APIs and schemas of one technology don’t correlate with another, analysts have been finding it hard to move data easily. This takes a toll on the time spent on converting and moving the data than to actually perform analysis on them.

Sprinkle doesn’t lock the data to the parent data source technology, it provides flexibility and mobility to the user’s business data. The tool updates with all leading open-source platforms to build analytics and data science applications in industry-standard programming languages.