Analytics

Prescriptive Analytics

Data analytics technology helps organizations make sense of an ever-increasing volume of data. As this technology matures, it gets better at delivering actionable insights and helping companies determine outcomes. Prescriptive analytics is a modern solution that builds upon other analytics technology and guides organizations to the right decisions for a particular situation.

Discover Which Source Brings in The Most New Opportunities for Your Business

Calculating the return on your marketing investment can be challenging and time-consuming. As there are various marketing sources and channels that create new sales opportunities, it’s important to know which ones are working best to help you meet your business goals.

The Rocket Behind Snowflake's Rocketship

Not a day goes by without questions from candidates, customers, and other interested parties about how we run Snowflake Engineering. I often hear: “Snowflake has been delivering a truly innovative, high quality product, and the pace of delivery is only accelerating. There must be a secret to it.” Indeed, we have a unique engineering team, and continue to hire world-class engineers. They are the driving force behind our products.

Insurers - Be Aware of the Hidden Exposures in assessing the economic impact of Climate Risk

Climate change is a challenge for insurers in some obvious ways, such as stronger and more frequent natural disasters. Yet there are also more subtle risks to monitor, including changes to insured assets, risks, and exposures. Climate impacts the production quality and quantity of insured consumable goods, their location, and their supply chains.

3 Reasons Extract, Load & Transform is a Bad Idea

Extract, Load, Transform (ELT) technology makes it easy for organizations to pull data from databases, applications, and other sources, and move it into a data lake. But companies pay for this convenience in many ways. ELT solutions can have a negative impact on data privacy, data quality, and data management.

Build/Buy in MLOPs for R&D Does "off-the-shelf" exist yet?

What kind of tools and infrastructure does a company need in order to build, train, validate and maintain data-based models as part of products? The straight answer is - “it depends.” The longer one is: “MLOps.” It is far too early to determine the “best” patterns and workflows for Data-Science, Machine- and Deep-Learning products. Yet, there are numerous examples of successful deployments from businesses both big and small.

Building a Single Pipeline for Data Integration and ML with Azure Synapse Analytics and Iguazio

Across organizations large and small, ML teams are still faced with data silos that slow down or halt innovation. Read on to learn about how enterprises are tackling these challenges, by integrating with any data types to create a single end-to-end pipeline and rapidly run AI/ML with Azure Synapse Analytics with Iguazio.