Systems | Development | Analytics | API | Testing

An Introduction to Flask-SQLAlchemy in Python

Efficient management of database interactions is one of the most important tasks when building Python web applications. SQLAlchemy — a comprehensive SQL toolkit and Object-Relational Mapping (ORM) library — is widely used in the Python ecosystem for this purpose. However, integrating SQLAlchemy with Flask can be a complex process. So developers created Flask-SQLAlchemy to provide a seamless way to use SQLAlchemy in Flask applications, making database management a straightforward process.

Cloudera and NiFi: Driving Data Ingestion and Processing Excellence

Empowering Data-Driven Organizations with Cloudera Flow Management 4 (powered by Apache NiFi 2.0) Apache NiFi has long been a cornerstone for data engineering, providing a powerful and flexible framework for data ingestion, transformation, and distribution. As a leading contributor to NiFi, Cloudera has been instrumental in driving its evolution and adoption.

Strategy Pattern: Definition, Examples, and Best Practices

Strategy is one of the most well-known design patterns, and luckily, it’s also one of the easiest to understand and use. That doesn’t mean the strategy pattern isn’t valuable. Quite the contrary: this pattern is incredibly powerful in enabling you to write code that is low coupled, easy to read and maintain, adheres to the SOLID principles and the dependency injection pattern. To help you understand the strategy pattern, this post covers the following.

Introducing Lineos, AI Powered by insightsoftware: Transforming Finance Workflows With Actionable Insights

Lineos reduces manual tasks and empowers finance teams to boost productivity and uncover hidden potential within their data RALEIGH, N.C. – Feb. 26, 2025 – insightsoftware, the most comprehensive provider of solutions for the Office of the CFO, today announced the launch of Lineos, a suite of AI-driven capabilities designed to enhance insightsoftware’s financial planning and analysis (FP&A), accounting, and operations products.

Yes, Qlik Has Changed - And That's Exactly the Point

I recently saw a post on LinkedIn that said, “Qlik isn’t the same company it was in 2016.” I’m pretty sure that it wasn’t meant as a compliment. But here’s the thing: they’re right. And that’s a good thing. Because if we were the same company we were in 2016, we wouldn’t be prepared for the challenges businesses are facing today. The world of data and AI has changed. Businesses have changed. So, of course, Qlik has changed too.

Federated API Management: Balancing Speed and Control

As the need for speed in business can seemingly be at odds with the need for control, organizations developing APIs today face a critical challenge: how can you empower developers to build and deploy APIs quickly while maintaining enterprise-wide governance and security? More traditional API deployment approaches are often to blame for why API initiatives fail to deliver the promised benefits as complexity and scale increase.

Tenstorrent Cloud Instances: Unveiling Next-Gen AI Accelerators

Today, we’re thrilled to announce the world premiere availability of Tenstorrent Instances via the Koyeb Serverless Platform. You can now access the Wormhole multi-chip solution in minutes to bring up and test frontiers of model inference performance. You've probably heard us say this: we're committed to bringing alternative accelerators to market to foster innovation in the AI infrastructure space.

The How and Why of Data Cleansing

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its quality, accuracy, and reliability. This process is crucial for businesses that rely on data-driven decision-making, as poor data quality can lead to costly mistakes and inefficiencies. By cleansing data (removing duplicates, correcting inaccuracies, and filling in missing information), organizations can improve operational efficiency and make more informed decisions.