Systems | Development | Analytics | API | Testing

Do you know how much data your company stores? Do you know the types of data being utilized for any given purpose? Can you picture how data flows from one system to another? The goal of data modeling is to help you understand aspects like these. By giving you a visual representation of data within your systems, data modeling tools help you better store, manage, and utilize your data by optimizing the underlying architecture.

2022 was without a doubt a landmark year for business intelligence (BI) and analytics. With continued development of innovative and sophisticated technologies such as contextual analytics, analysis of our business data is more accessible than ever before. Many of these same trends will continue to grow into 2023, but the data analytics space is ever evolving.

Change data capture (CDC) identifies and captures data changes in source systems. Here’s a list of the best CDC tools.

Snowflake customers leverage the Data Cloud to bring all their data together and capitalize on the near-infinite resources of the cloud. But how can this data be used to look ahead? How can we use yesterday’s evidence to plan for tomorrow? The answer—time series forecasting. Time series forecasting is one of the most applied data science techniques in business. It is used extensively in supply chain management, inventory planning, and finance.

When researching your next ETL and ELT tool, you should consider Keboola as one of the best Fivetran alternatives. In this blog article, we’re going to compare Keboola and Fivetran side-by-side and show you how Keboola can simplify your data operations. We’re going to evaluate both tools based on these critical product features: Here is a quick breakdown summary of the comparison between Keboola and Fivetran: ‍

Happy New Year from the Yellowfin team, and welcome to our 2023 wrap-up! Following a year full of product feature updates, company changes and new initiatives, this blog provides a helpful summary for all our customers and followers on our future 2023 product roadmap for the Yellowfin embedded analytics suite, and a look back at last year’s biggest news.

In general, the concepts of data literacy and creating successful data pipelines seem totally disconnected. Data literacy involves insuring that data consumers have the knowledge and capabilities to understand and interact with data in a way that will provide them with the answers and value they need to do their jobs and benefit their organizations. While data pipelines require technical expertise to move, connect, and store data across the company's data ecosystem.

This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.