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Seven Ways to Scale a Data-Driven Culture in Your Organization

Without an overarching company data culture, even the best technology tools won’t get you where you want to go, say the co-founders of Data Culture. Data isn’t just a tech solution. For Gabi Steele and Leah Weiss, founders of the consultancy Data Culture, it’s also a “people” solution. Even within companies that enthusiastically embrace a cloud-based modern data stack, a substantial gap often exists between the business and data sides of the organization.

Scalable Data Stack Helps Welcome Tech Empower Immigrants

Welcome Technologies builds more robust data pipelines with Fivetran to propel its work on improving the lives of immigrants through a data-first approach. Key Takeaway With its data-first approach, Welcome Tech is developing machine learning and security models to better serve the immigrant community. After building and maintaining a Postgres connector, Welcome Tech brings on Fivetran to scale its data architecture.

Fivetran Receives ISV Partners Innovation Award From Databricks

We’re honored to win this prestigious award, and we’re doubling down on the Lakehouse architecture with Databricks SQL analytics plans. Fivetran is the proud recipient of the Databricks ISV Partners Innovation Award as announced at this week’s Data & AI Summit Europe event. The award recognizes how Fivetran has collaborated with Databricks to empower data professionals to accelerate time to insights with Delta Lake and the Lakehouse architecture for the modern data stack.

Improve Your Business Intelligence With a Modern Data Stack

F5 Networks modernized its data stack, boosted time to insight, and placed actionable data in the hands of the right decision-makers. F5 Networks is a Seattle-based application services and application delivery networking company. Because its revenue depends on speed and accuracy, the company is always looking for ways to improve business insights and support data-driven decision-making.

Data Egress Cost Analysis

Understand the impact of data transfer and egress costs across Microsoft Azure, Amazon Web Services and Google Cloud Platform. One of the questions most frequently asked by cloud-savvy, price-aware customers goes something like this: OK, so we like that your tool makes it easy to integrate our cloud database and storage in our centralized data warehouse, but I know our budget will be scrutinized for total cost of ownership (TCO), including our data egress costs.

Five Reasons to Consider a Modern Data Stack

Fivetran co-founder and CEO George Fraser shares the importance of the modern data stack and five developments he’s eagerly following. When Thomas Edison switched on his first working light bulb, even he could not have predicted that this new technology would eventually revolutionize every aspect of modern life.

Four Ways a Modern Data Stack Can Fuel Results

When record-breaking demand exploded with COVID-related purchases, e-Commerce company Drizly thrived thanks to its modern data stack. Drizy is the world’s largest online alcohol marketplace. From the company’s website and app, users can order their favorite beers, wines and liquors from local retailers, and have them delivered in less than an hour.

Demystifying Cloud Data Egress Costs

Understand the impact of data transfer and egress costs across Azure, Amazon Web Services, and Google Cloud platform in data integration One of the most frequent questions asked by cloud-savvy, price-aware customers is something like: Ok, so we like that your tool makes it easy to integrate our cloud database and storage in our centralized data warehouse, but I know our budget will be scrutinized for Total Cost of Ownership (TCO), including our data egress costs.

Data Lakes vs. Data Warehouses vs. Data Marts

Let’s precisely define the different kinds of data repositories to understand which ones meet your business needs. October 29, 2020 A data repository serves as a centralized location to combine data from a variety of sources and provides users with a platform to perform analytical tasks. There are several kinds of data repositories, each with distinct characteristics and intended use cases. Let’s discuss the peculiarities and uses of data warehouses, data marts and data lakes.