The latest News and Information on Business Intelligence, Reporting and related technologies.
The 2022 Australian Open men’s singles final between Rafael Nadal and Daniil Medvedev was epic! I watched it in Australia, which meant I was up until 2 a.m. on a Sunday night. Monday morning’s dog walk was sub-joyful. Medvedev seemed unplayable, taking the first two sets comfortably. But Nadal is a legend for a reason. Point by point, he overran his rival to make history.
The FinTech revolution is truly transforming the way that we manage our money, bringing new online banks, new models for insurance provision, new ways to access loans, and much more. It rests on a number of pillars, but one of the most important is that of big data.
Nowadays, easy access to data is table-stakes for high-performing companies. Easy access doesn't come for free, though: it requires investment and a careful selection of tools. For young companies like us, the question is how much? And when do you make that investment? Having grown to ten people, several without engineering backgrounds but with strong data needs, we decided 2022 was going to be that time.
Microsoft BI is a powerful game-changer for business intelligence solutions that are widely used for data analysis and reporting. It is a unified self-service that delivers a great depth of data insights by combining interactive data visualizations with intuitive user experience. Whether you are a business enthusiast or an owner who likes to keep a tab on all things in a single dashboard, Power BI allows you to visualize and analyze your data dynamics like never.
Business Intelligence is essentially an umbrella term that includes infrastructure, best practices, and applications needed to analyze data and support decisions. In the age where data holds unlimited transformative potentials, hospitals and healthcare institutions are diving headfirst to harness the power of data through business intelligence (BI) services.
Spark is one of the most widely-used compute tools for big data analytics. It excels at real-time batch and stream processing, and powers machine learning, AI, NLP and data analysis applications. Thanks to its in-memory processing capabilities, Spark has risen in popularity. As Spark usage increases, the older Hadoop stack is on the decline with its various limitations that make it harder for data teams to realize business outcomes.