Augmented analytics is one of the top 10 technologies Gartner identified with the potential to cause significant digital disruption in the next three to five years. The hallmark of augmented analytics is its high reliance on AI and ML technologies. AI and ML together will transform enterprise Data Management in the coming years, and many […]
Serverless Computing Use Cases
The uniqueness of serverless computing is its ability to survive without the presence of physical machines and systems software. In the serverless computing world, the client subscribes to a set of services including special “APIs and web services” that software developers can use to quickly build useful and scalable architectures for on-demand computing services. Serverless […]
Data Management vs. Data Science
The shift in the business perception of data has now catapulted Data Management into new heights. Data Science is a core component of Data Management now, but Data Management and Data Science are often seen as two different activities. Working among data analysts, data engineers, and DBAs, data scientists spend their time getting the data […]
Emerging Cloud Computing Technologies
It has taken many years for cloud computing technologies to mature and become mainstream in global businesses. Now the skeptics have stopped questioning the long-range sustainability of the cloud ecosystem, but it remains to be seen how allied technologies like edge, serverless, IoT, AI, and big data can together fulfill enterprise business needs. Many cloud […]
Automation and AI: Challenges and Opportunities
Businesses across the globe are fascinated with the idea of AI and automation because this advanced technology promises operational efficiency, enhanced processes, and substantial cost savings. However, AI and its allied technologies have also created uncertainties, confusion, and doubts about the human capability for adopting, deploying, and executing these magical systems in actual business situations […]
Deep Learning Updates: Machine Learning, Deep Reinforcement Learning, and Limitations
In recent years, some astonishing technological breakthroughs in the field artificial intelligence (AI) and its sub-field deep learning have begun to train machines to behave like humans. As machines are increasingly emulating complex cognitive functions such as deductive reasoning, inferences, and informed decision-making, robots functioning as humans are a reality in many industry practices today. […]
Data Architecture and Artificial Intelligence: How Do They Work Together?
Artificial intelligence (AI) is rapidly gaining ground as core business competency. Today’s machine learning (ML) or deep learning (DL) algorithms promise to revolutionize business models and processes, restructure workforces, and transform data infrastructures to enhance process efficiency and improve decision-making throughout the enterprise. Gone are the days of data silos and manual algorithms. However, widespread […]
Data Governance and Serverless Computing
Some of the latest buzz in the big data world is centered around the complexity of on-premises, Hadoop technology implementation, and so enterprises are getting restless and moving to the cloud. In an increasingly cloud-friendly business landscape, serverless computing may hold more promise than retrofitting Hadoop. More and more global businesses are moving to the […]
Data Fabric Use Cases
Data is expanding in volume, variety, and sources; therefore, so is the business need for trustworthy, accurate, and timely data for on-demand “competitive intelligence.” A data fabric offers a long-range technological solution for handling the myriad challenges that come with such a complex data ecosystem. This “converged platform,” designed with a unique architecture and a […]
Fundamentals of Machine Learning Enabled Analytics
The famous theoretical physicist Stephen Hawking said, “It’s tempting to dismiss the notion of highly intelligent machines as mere science fiction.” Artificial intelligence (AI), the game-changer technology of the global business world, comprises three distinct sub-disciplines: machine learning (ML), natural language processing (NLP), and cognitive computing. Automated solutions in business analytics use all these sub-technologies, […]