Siteline Data Analytics for Automated Insights at Scale. More than Reports.
Optimize your business strategy with composable data analytics. Support your teams with data-driven decisions.
Data analytics platform trusted by customers worldwide
Benefits of data analytics tools
Insights pilot
Our AI data analytics operates like your co-pilot or assistant providing timeley insights.
Move quickly with precision
By constantly observing and analyzing data your employees can move to data driven decision making.
Unify for better outcomes
Integrate, transform, mine, orchestrate and store your data in a single easy to use platform.
How it works
This data analytics solution guide walks through the basic elements of data analytics strategy. See how customer data analytics works and supports a decision making framework.
Authentication
Sign in to open the Intelligent Automation Platform Manager, then click on Siteline Analytics, which allows you to design and build automation processes that integrate your data, analytics and operations.
Create New Connection
Once successfully logged into Siteline Analytics, open the wizard to locate the applications where your data is stored. The wizard has over 340+ connectors.
Create New Destination Connection
Please locate your database and connect where the information is stored.
Field Descriptors, Formatting & Queries
Based on the specific business or functional outcomes, build the required query or queries.
Dashboard and Reports
Develop your unique dashboard from our list of dashboard templates.
Execute
Click activate to start data mining, observing the data and generating insights.
Scale
To connect other data sources to analyze and observe follow the six steps above.
Key features of data analytics
Unified Data Management
Fully Automated Governance
Real Time Dashboards
Self Select Prediction Modelling
Integrated Orchestration
Embedded No Code Integration
Ontology Mixing
Secure On-Premise Connection
Explore demo and use case videos
Siteline Data Analytics - Tour and Explainer Demo
- Link all of your data, objects, and models together
- Data and process mining for automation insights
- AI-driven models and action orchestration to drive processes
- Multi-temporal based reporting and analytics
- Build automated data health and quality management directly into the places where data needs to be worked on.
- Quickly profile large data sets to understand data health used to drive decision outcomes.
Building Custom Reports In Sightline - Demo Video
See how to combine multiple data sources into Siteline and use your favorite report creation tool to get the analytics the way you want.
Explore handpicked resources
How Professionals Identify The Best 'New' Customer
Read how to increase revenue with AI and predict customer preferences and buying patterns. Easily understand what the customer wants.
How Predictive Customer Lifetime Value Drives Revenue
Understand how to use predictive customer lifetime value to gather historical data, get more sales, and increase customer retention.
Forecast Revenue Churn with Easy-to-Use Calculator
Try the ROI Forecasting Calculator to estimate how much savings or ROI your organizations can expect from Predictive AI Investment.
FAQ about Data Analytics
A data analytics platform is a comprehensive system that integrates various data analytics tools to process, analyze, and visualize large datasets, enabling businesses to derive valuable insights.
Data analytics tools are individual software applications or programs used for specific analytical tasks, while a data analytics platform encompasses a broader range, offering a unified environment for various tools to work together seamlessly.
A data analytics solution refers to a holistic approach, combining tools, processes, and strategies to address specific business challenges through data analysis.
Yes, explore data analytics case studies with solutions to see practical examples of how businesses have successfully implemented data analytics to solve specific problems and achieve positive outcomes.
AI data analytics involves leveraging artificial intelligence and machine learning algorithms to enhance data analysis processes, uncover patterns, and make predictions for more informed decision-making.
Customer data analytics involves analyzing customer-related data to gain insights into their behavior, preferences, and needs. It is crucial for businesses to personalize offerings and improve customer experiences.