Analytics

Consider the following when choosing database processing options.

The Google Cloud Public Datasets program recently published the Python Package Index (PyPI) dataset into the marketplace. PyPI is the standard repository for Python packages. If you’ve written code in Python before, you’ve probably downloaded packages from PyPI using pip or pipenv. This dataset provides statistics for all package downloads, along with metadata for each distribution. You can learn more about the underlying data and table schemas here.

If you already have some brand awareness, so people know who you are and what you do, there are three ways that you can accelerate your sales in a virtual environment.

Getting a spot in SERP features takes study & strategy. Learn how experts optimize their content to rank in featured snippets and other SERP elements.

Use database connectors to uncover insights about your operations.

Today, more than ever, line-of-business users responsible for managing working capital need actionable insights in real-time. At the same time, IT/data teams want to accelerate projects, as well as modernize and integrate their data architectures and analytics, while managing risks and costs.

The velocity of change is accelerating. The rate of change businesses are experiencing is just astounding. As many organizations have experienced during the pandemic, especially in their supply chain, the need for the data environment to be able to deliver faster is now mission-critical for all! We need better data—but at a rate that’s much faster than before. Businesses need their data teams to become more responsive to changing data demands. That means they need agility.

Cloud-based data warehouses offer unlimited scalability with the best features of both traditional data warehouses and data lakes.

For many businesses in 2020, the increased use of cloud providers and online services has been essential to keeping the lights on in virtual environments. This has prompted companies to overcome the inertia and red tape surrounding SaaS, PaaS and other “aaS” products.

One of Xplenty's most rewarding features is its ability to enact low-code and no-code digital transformation. Even with no experience in ETL or data integration, non-technical users can take advantage of Xplenty’s intuitive drag-and-drop interface to build robust, complex data pipelines to a data warehouse or data lake in the cloud.