Companies of all sizes are looking for faster and easier ways to take advantage of data through analytics and BI. In particular, knowing who your customers are, how they interact with your business, products and services is a modern necessity. In a customer-centric world where data can help improve the overall customer experience and relationships, […]
Photo by Myriam Jessier on Unsplash The modern data stack (MDS) is a new approach to data integration capable of saving your engineers time while allowing both engineers and analysts to focus on high-value pursuits. With a suite of tools to support data integration, the modern data stack will free your teams of monotony while […]
Photo by Windows on Unsplash It seems like it might be finally happening. Data engineering is finally getting a little bit of the data lime light. Which makes sense. The data being stored and analyzed is not only becoming more voluminous but its speed, complexity and variety are also increasing. Making it difficult to wrangle. With […]
Photo by Samuel Sianipar on Unsplash In the business world, cloud technology has become more and more dominant in recent years. Right now, research shows that about 50% of all business data is stored in the cloud, which just demonstrates the importance of external data sources and their place in the modern business environment. In […]
Data is continuing to prove to be a valuable asset for businesses of all sizes. I say that both from the fact that consulting firms like McKinsey have found that in their research companies that are using AI and analytics can attribute 20% of their earnings to it. Similarly, I have been able to consult for […]
Photo by Karo Kujanpaa on Unsplash By Travis Wolf Introduction — “What is MLOps? — DevOps for ML” — Kaz Sato Challenges arise as the production of machine learning models scale up to an enterprise level. MLOps plays a role in mitigating some of the challenges like handling scalability, automation, reducing dependencies, and streamlining decision making. Simply […]
Background In 2014 a group of Google researchers put out a paper titled Machine Learning: The High-Interest Credit Card of Technical Debt. This paper pointed out a growing problem that many companies might have been ignoring. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the […]
Machine Learning Operations, or MLOps is a relatively new concept. Starting back in 2014 there were rumbling of the challenges connected with deploying machine learning models into production. This started to lead to machine learning platform start-ups like DataRobot and H2o.ai gaining a decent amount of traction and funding. Somewhere around 2018 the term MLOps […]
Photo by SELİM ARDA ERYILMAZ on Unsplash The rise in self-service analytics is a significant selling point for data warehousing, automatic data integrations, and drag and drop dashboards. In fact, in 2020, the largest software IPO this year was a data warehousing company called Snowflake. The question is how do you get your data from external […]
Data warehousing was introduced in 1988 by IBM researchers Barry Devlin and Paul Murphy. Since then the concept has evolved and taken on a life of its own. Increasing challenges and complexities of business have forced data warehousing to become a distinct discipline. Over the years this has led to best business practices, improved technologies, and hundreds […]