Analyzing data as it is created or changes? Is that possible? Now it is, with streaming analytics, which monitors and responds to continuously flowing data from connected devices and live data channels like the sensors, machine logs, relational databases, social media feeds, location data sources, and so on. The core differentiator of streaming analytics is […]
A Brief History of Data Science
The term “Data Science” was created in the early 1960s to describe a new profession that would support the understanding and interpretation of the large amounts of data which was being amassed at the time. (At the time, there was no way of predicting the truly massive amounts of data over the next fifty years.) […]
So You Want to be a Big Data Analyst?
With the increasing use of big data by organizations in every field, the need for big data analysts will continue to grow. Big data analysts examine vast amounts of varied data. They uncover hidden patterns, customer preferences, and market trends. One of the primary differences between a big data analyst and a data scientist is […]
Enterprise Analytics Trends
Evan Terry, Chief Analytics Officer at Velocity Mortgage Capital said that enterprise analytics technology is increasingly sophisticated, due to machine learning, artificial intelligence (AI), and streaming analytics, but you can’t benefit from these advancements without a solid foundation. “There’s a real interplay there between the foundational and the advanced.” Terry discussed these interplays during his […]
A Brief History of Analytics
Historically speaking, a simple definition of analytics is “the study of analysis.” A more useful, more modern description would suggest “data analytics” is an important tool for gaining business insights and providing tailored responses to customers. Data analytics, sometimes abbreviated to “analytics,” has become increasingly important for organizations of all sizes. The practice of data […]
The Distributed Cloud and Data Governance
The business of Data Management embraced new complexities when diverse types of data started flowing in—in huge volumes through multiple data channels and in real time. Analysis of very high-speed, high volume, multi-type business data necessitated the growth and development of advanced Data Management technologies and tools, and cloud computing technologies were born out of […]
Next Generation Business Intelligence: Customer-Driven Success
In the customer-driven era, business success depends on how quickly a business can respond to a customer demand. The more that businesses become reliant on real-time outcomes, the more they will seek next-generation (next-gen) BI deployments. Traditional Business Intelligence (BI) platforms were high-cost and time-intensive applications. The current trend in BI is to move toward […]
Knowledge Graphs, Ontologies, and AI
This past fall, all aspects of the computable knowledge structure KBpedia – its upper ontology (KKO), full knowledge graph, mappings to major leading knowledge bases, and 70 logical concept groupings called typologies – became open source. Making big strides in increasing definitions and mappings has been a main focus of KBpedia v. 1.60. As it always […]
Industry 4.0: Make Data-Driven Decisions Immediately
What if a cyber-physical world — fueled by data — shortened production and manufacturing decisions to the time it takes to adjust a thermostat’s temperature? This just begins to describe Industry 4.0. According to a recent McKinsey article, Industry 4.0 “expects to deliver between $1.2 and $3.7 trillion in value.” Meanwhile, according to Riasat Noor, […]
Machine Learning vs. Deep Learning
The debate on machine learning vs. deep learning has gained considerable steam in the past few years. The fundamental strength of both these technologies lies in their ability to learn from available data. Though both of these offshoot AI technologies triumph in “learning algorithms,” the manner in which machine learning (ML) algorithms learn is very […]