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Are you executing data replications and backups? Building ETL data pipelines? Ensuring the data ingestion is running smoothly? Or simply building an ad hoc dataset for your machine learning task? Using a data mapping tool can shave hours off your engineering work in all four use cases. In this article, you will learn.

The recent advances in deep learning neural networks are pushing beyond what we thought AI technology could do. Heck, with DALL-E 2 winning art competitions and ChatGPT passing anything from New York’s Bar exam to Advanced Sommelier exams, modern AI technology is performing better than the average Joe. Which begs the question: How can AI solutions be used to improve business outcomes?

North Labs is an end-to-end data consultancy enabling business transformation in the areas of DevSecOps, Data Engineering, and Cloud. The team serves highly regulated industries with their mission-critical digital implementations, while simultaneously safeguarding data and ensuring compliance. We talked to Daniel Rothamel, Cloud Data Delivery Engineer at North Labs, to better understand how the joint solution of Snowflake, Keboola, and North Labs helps their customers to get more value from their data.

Apache Airflow and dbt are both popular contenders for the best workflow management tool in the Modern Data Stack. However, when it comes to picking the best tool, the differences are not trivial, and the use cases for each tool are quite different. In this article, we’ll compare dbt vs Airflow on multiple points.

Amidst growing inflation, big and small businesses are looking to cut costs to stay competitive. According to Gartner, reducing IT costs is a top priority for 40% of CFOs. Cost-saving initiatives usually focus on firing people or getting rid of un(der)used technology. This might work in the short term. For example, the IT cost reduction strategy of renegotiating service level agreements and software licenses with your service providers can impact the bottom line.

With so many ETL solutions on the market that help you streamline and automate your extract, transform, and load data pipelines, it’s hard to find the best tool for your organization. In this article, we'll simplify your ETL tool comparison by highlighting the best tools on the market right now and outlining seven criteria you can use to decide which one to use. Use this free downloadable checklist and evaluate the best tools yourself.

Data migration can be a time-consuming and error-prone process. But with the right data migration tool, you can automate the migration workflows, ensure high data quality and save a lot of that precious time for more value-generating tasks. In this blog, we'll cover 7 of the best data migration tools available on the market today, along with their pros, cons, and ideal applications.

Running a Shopify ecommerce store can be challenging - you have to take care of marketing, supplies, deliveries, returns, complaints, and every little thing in between, so you easily lose focus on what matters and brings value. Luckily, we have an easy solution! Keboola and Snowflake have partnered to bring you a no-code solution that turns your Shopify data into an insights machine in just 45 minutes. Let's take a look and try it hands-on! You might say.

Microsoft Power BI is a fantastic tool for data visualization and business intelligence. But as any data analyst can attest, before you can build metrics and dashboards, you need to spend more than 1/3 of your time preparing and cleaning the dataset for your Power BI instance. Luckily, there is a better way to cut down on this time-consuming task. In this article you will learn.

Who doesn’t love Apache Airflow? The Python-based open-source tool allows us to schedule and automate workflows with DAGs (Directed Acyclic Graphs). Data teams use Airflow for a myriad of use cases: from building ETL data pipelines to launching machine learning apps. The open-source tool makes workflow management easy: it is extensible, easy to monitor from the intuitive user interface in real time, and it allows you to build dependencies between jobs.