Real-world success stories illustrate the benefits of a modern data stack, from lower engineering costs to greater data literacy.

A cloud-native data stack frees up Clari’s one-man analytics team to drive data innovation and revenue.

Bring life to your data visualizations and dashboards to create compelling, crowd-pleasing presentations that your managers will love.

Harnessing data to drive business decisions is a key competitive advantage. For next-generation data analytics, follow these three principles.

Bring life to your data visualizations and dashboards to create compelling, crowd-pleasing presentations that your managers will love.

A cloud-native data stack equips a construction company with better business intelligence to guide planning and decision-making.

Lifetime Value vs Acquisition Cost: The LTV:CAC ratio, a golden metric scrutinized by VC’s and Growth Marketers alike, requires not just the integration of dozens of data sources, but also the know-how to build reports that make sense to industry pros.

For high-growth companies, building a focused, priority-driven analytics team is mission-critical.

Data Scientist Jay Kotecha and Ecommerce Director Ollie Scheers share how they use data to meet Huel’s mission: Make Customers Happy.

Five leading experts share their insights on what’s ahead for the data industry.

Why you should use Fivetran history mode for historical analysis over alternative solutions.

It's important to understand the uses and abuses of streaming infrastructure. Apache Kafka is a message broker that has rapidly grown in popularity in the last few years. Message brokers have been around for a long time; they're a type of datastore specialized for "buffering" messages between producer and consumer systems. Kafka has become popular because it's open-source and capable of scaling to very large numbers of messages.

With automated data integration, CaliberMind uncovers data insights for customers. As a Customer Data Platform (CDP), CaliberMind delivers data-driven insights to its customers. To do so, it must connect to its customers’ data sources, extract, process and transform the data, run it through specially designed analytic models, and, finally, present data back to the customer as insights. CaliberMind uses Fivetran to offload the task of ingesting data from its customers’ applications.

With Fivetran and Databricks, Slice reallocates the efforts of three data engineers to mission-critical projects and adds a data science team.

A data pipeline is a series of actions that combine data from multiple sources for analysis or visualization. In today’s business landscape, making smarter decisions faster is a critical competitive advantage. Companies desire their employees to make data-driven decisions, but harnessing timely insights from your company’s data can seem like a headache-inducing challenge.

Thinking of building out an ETL process or refining your current one? Read more to learn about how ETL tools give you time to focus on building data models. ETL stands for extract-transform-load, and is commonly used when referring to the process of data integration. Extract refers to pulling data from a particular data source. Transforms are used to make that data into a processable format. Load is the final step to drop the data into the designated target.

Want to look at how data has changed over time? Simply enable history mode, a Fivetran feature that data analysts can turn on for specific tables to analyze historical data. The feature achieves Type 2 Slowly Changing Dimensions (Type 2 SCD), meaning a new timestamped row is added for every change made to a column. We launched history mode for Salesforce in May and have been delighted with the response.