Snowflake's mission revolves around making data accessible, usable, and valuable to everyone. One of the pillars that have made Snowflake an industry leader is its unwavering commitment to being easy to use and turnkey.

As data-leveraging tools grow more powerful than ever, so has our desire for quick and convenient access to insights. Tableau’s mobile layout feature allows users to quickly reference the data they need regardless of circumstance. Read along for several tips to seamlessly convert your existing Tableau dashboards to a mobile layout in a way that is digestible and powerful for your audience.

Usability testing is a crucial step in designing any product or application. For our team developing Clear Path , designing the usability tests was a very important part of the process. Since our Jira app was a new application being developed from scratch, there is even more of a need to understand the user experience and improvements that can be made based on user feedback. Before conducting the tests, designing the usability test is equally important to ensure you are receiving the information that would help make your product better.

When first designing our usability test script, there was discussion about whether to use a usability test or user acceptance test (UAT). Although these types of tests are used interchangeably, they have differences that need to be considered. Being a new app, it was a question for our team on whether to do usability testing or user acceptance testing. So, what is the difference between these two types of tests?

In a world increasingly reliant on digital information, the ability to harness and interpret your data is a crucial aspect of maintaining a competitive edge. This is where Honeycomb Analytics comes in. We provide a comprehensive solution designed to centralize your data into a usable and reliable platform, providing analytics at your fingertips. Our system is designed to decrease the time to value for clients who need consumable data more than complex platforms and integrations. Harness the power of data analytics technology to make informed decisions quickly and modernize your business approach with a data-oriented strategy for success. New insights can be found in even the most familiar places, and these insights might be the key to your business staying ahead in today's fast-paced markets.

You have two choices for building the user interface for your Forge app – the UI kit, and custom UI. The UI kit allows you to create a straightforward UI using a set of Atlassian-supplied components, put together using relatively simple code. Custom UI gives you more room to use Atlassian-supplied and third-party hooks, components and such, while also allowing you to employ more complex HTML, CSS, static resources (such as images) and source code, all of which can be hosted in Atlassian’s cloud with custom UI but not the UI kit. Both types of UI involve writing code in a React-like pattern, which makes sense in that various components available from Atlassian are based on React.

In a prior installment of this blog [1], we discussed getting your Forge app up and running in a "Hello, World!" way on a test Atlassian instance. Now, perhaps your company has an Atlassian instance that employees use daily, and you'd like to test your Forge app in the real world by installing it on that instance. Another scenario is that you’re now ready to have customers for your app, so you need to distribute it to them.

Forge is Atlassian’s next-generation framework for building apps that integrate with Confluence, Jira, or Jira Service Management. Forge provides Web UI elements, APIs and deployment environments that enable developers to create fully-featured apps within Atlassian’s cloud infrastructure through the use of JavaScript, HTML, CSS and other Web technologies. Forge apps can be distributed via the Atlassian Marketplace as software to which any Atlassian Cloud customer can subscribe.

Moser Consulting was recently tasked with reducing costs and ensuring more consistent SLA compliance in a company's Snowflake environment. While Snowflake differs from traditional and other cloud databases, it is still a SQL-based database, and many of the same tuning techniques apply. However, understanding Snowflake's architecture is crucial, as it offers unique cost-saving opportunities not found in traditional databases.

Recently, I stumbled upon a blog by Felipe Hoffa that detailed using Cloudflare R2 as the data storage location for external tables in Snowflake. I had a project that required less than 5 GB of storage per month, and I wanted to avoid paying for storage if possible. Therefore, I decided to experiment with Cloudflare's free tier as my data lake. The results were nothing short of impressive.

For the second year in a row, Snowflake has been named the Database of the Year by DB-Engines. Over the past couple of years, it has climbed the popularity rankings, currently sitting at #11. Snowflake is a cloud data platform designed for analytical, AI, and ML use cases. As a cloud-native solution, its architecture differs significantly from traditional databases like SQL Server, Oracle, MySQL, and PostgreSQL.

Data is everywhere, and that’s not going away any time soon. Learn about data analytics career opportunities and why now is a great time to get started.

Data management is essential for businesses that collect and store data. What processes can you take to keep data safe and useful for your business?

As of Oct 11, 2022 Mainstream Support has ended for SQL Server 2017.

Data management, data analytics, and data analysis… together, they make up the backbone of business, driving optimization, improving workflows, and boosting return on investments.

Data security is a top priority for IT companies to ensure that sensitive information is not compromised, lost, or corrupted.

See what it takes to start a successful career in the tech industry and which path is the best fit for you.

Companies have more data than they’ve ever had before. Data Management as a Service (DMaaS) can provide teams with a secure solution to data management.

Data equity applies an equity-centered lens and mindset to ensure data is collected, analyzed, interpreted, and shared with diverse stakeholders without bias or exclusion.