Andrew Chen

AI-Driven Analytics with IT/OT Data: Powering Next-Gen Manufacturing

The World’s Most Innovative FinTech Companies Need the World’s Easiest Data Cloud

Moving Customer-Centric Experiences Forward with Data and AI for Retail

In this article, we’ll break down the core components, benefits, tools, and challenges of modern cloud analytics and explore why it’s replacing legacy BI for good.

To help you make a more informed decision, we’ve reviewed official documentation, analyzed real-world user feedback from forums and review sites, and compiled practical insights into Tableau’s pricing. Whether you’re a startup, enterprise, or solo analyst, this guide will give you the clarity needed to evaluate Tableau’s true cost and value.

In this article, we’ll explore what KPI dashboards are, why they matter, and how to build them effectively.

Whether identifying bottlenecks in a supply chain or predicting customer churn, visual analytics enables users to ask better questions and get clearer answers without relying entirely on data science teams.

This article explores different types of pie charts, real-world use cases, and practical examples across industries to help you use them effectively in your own work.

In this article, we’ll explore the fundamentals of big data analytics, contrast it with conventional analytics, examine its key architectures and technologies, review leading tools and use cases, and address the benefits and challenges organizations face.

This guide covers 20 of the most commonly used charts and graphs, along with practical use cases and tips to help you decide when and how to use each.

This guide will walk you through the fundamentals of CRM analytics, explore its types and use cases, highlight key metrics, recommend top tools, and show you how to get started quickly and effectively.

This article will define data analytics, explore its importance, outline various types and methodologies, introduce essential tools, and highlight real‑world applications.

In the following sections, we’ll explore its objectives, core components, real-world applications, and future directions.

In the sections that follow, we’ll define AI predictive analytics, explore its core components and applications, and examine real‑world examples and future trends.

In this article, we’ll define what an analytics strategy is, explore why it’s essential, and guide you through building your own from the ground up.

Empower your end-users to build smarter reports with AI - right inside your app.

Here’s how startups can harness modern analytics tools like Explo and Snowflake to deliver impactful insights and gain a lasting competitive edge.

Explo named G2’s Spring 2025 “Momentum Leader” and #1 in Usability, Customer Relationship, and Implementation for Data Visualization

Imagine logging into a dashboard that feels like it was built just for you—highlighting the exact metrics you need, structured in a way that makes sense, and fully customizable to match your workflow. That’s the power of a custom dashboard builder.

User-facing analytics is the seamless integration of data-driven insights directly into products, applications, and platforms, designed for end users rather than internal teams.

Choosing the right Business Intelligence (BI) tool can feel like picking between two powerhouses—both Looker and Tableau bring a lot to the table, but they do it in very different ways. If you've ever struggled to decide between them, you’re not alone.

Tableau has been a dominant force in data visualization for years, offering stunning dashboards and deep analytics. But then there’s Sigma—a newer, cloud-native BI tool designed for teams that live and breathe spreadsheets.

A real-time dashboard is a digital interface that continuously updates data from multiple sources, providing users with live insights into key business metrics.

This guide breaks down everything you need to know—from choosing the best SQL dashboard tool to the top platforms that make analytics effortless. Let’s dive in.