Anant Corporation Blog: Our research, knowledge, thoughts, and recommendations about building and managing online business platforms.
Data mining is the practice of gathering and examining large databases to produce new information and predict future outcomes. Modern businesses rely on massive amounts of data, so much so that an IDG survey of 70 IT and business leaders recently found that 92% of respondents want to deploy advanced analytics more broadly across their organizations. This post will discuss some of the benefits of data mining that these leaders saw within their organizations.
In one of my earlier articles, I talked about why your company or organization should adopt Sitecore as your Experience Platform. It’s a good platform for users, content authors, and developers to create compelling and engaging digital experiences as well as collect information on website traffic. Machine learning and analytics in personalized content are two of the most compelling features of Sitecore. In today’s world, companies, particularly the Fortune 500, require real-time analytics to help drive stakeholder goals.
In today’s fast-paced technological society, we often hear about how artificial intelligence and machine learning are emerging as powerful techniques for accelerating data analytics amongst a wide variety of business platforms. But what exactly is Machine Learning, and how is it being implemented in platforms? How exactly can we harness the power that Machine Learning brings to create more robust tools to benefit clients?
This is the third part of our series covering some of our favorite Business Intelligence (BI) tools. Our previous two posts covered Metabase and Redash. In this post, we will cover Tableau, a very popular BI tool that came to be very prominent during the last 10 years as the number, and variety, of BI tools, surged to a wave of popularity, and to some extent, hype. Tableau has been recognized as a leader in the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms for six years in a row.In this series we will cover the four following applications:
Spark,Mesos, Akka, Cassandra, Kafka, Kubernetes? If you don’t already know what these mean and you have no goal or objective to make software that works at a global level, then you don’t need to be reading this article at all. Seriously, it’ll be a waste of your time. These technologies, now open sourced, originated from the extremely high-end university research laboratories of the University of Berkeley and the halls of high-tech companies such as Google, Twitter, LinkedIn, and Facebook. They were built for different purposes for their creators but now being available to the public, they have been flourishing on their own in the wild ether of the Internet. Why would any CIO, CTO, CMO, or a CEO consider these technologies?