With data being collected by organizations at a staggering rate, the demand for analytics to leverage the insight from this data is growing just as fast. Big data can viewed as a gateway to new opportunities, as a means of managing risks, or as a tool to improve business sustainability. Oftentimes, big data is associated with two keywords: analytics and technologies. These keywords represent an evolving suite of trends – from descriptive, predictive and prescriptive analytics to the application of Machine Learning, and Cloud technologies. Continuously monitoring these trends in analytical approaches and technological breakthroughs in the context of Big Data and applying them to produce business value is the key to survival in this Read more
Posts Tagged 'analytics'
The Internet of Things. Location-based services. Automated reasoning. Social media. Wearables. Analytics. I could extend this list of “game-changing” technologies, and so could you. What’s a CEO, CIO, CTO, CFO, or business unit president to do? Especially when they go to an investor conference and they’re asked to explain “the game-changing technology plan”? Those who work in the C-suite need smart people, budgets, and technology solutions to impact their business processes and overall business model. In other words, game changers need context; otherwise, C-suite(rs) end up chasing “the next great things,” which is what many companies have done for decades. Remember business process reengineering, Six Sigma, matrix management, and management by objectives? Who created Six Read more
Analytics — deep, predictive, operational, (insert preferred flavor here) — has climbed to the top of business executives wish lists in the past few years. The explosion of big data from social media sources and the coming supernova from the Internet of Things promises complete understanding of customer needs as well as the prediction/influencing of future behavior. With sufficient data, best of breed algorithms, faster computers, and emerging deep learning approaches — statistical correlation will become a largely exact science. Understanding causation will become an unnecessary luxury. Welcome to the analytics nirvana. Of course, inspiration and implementation often diverge. The day-to-day practicality of big data analytics continues to raise ongoing challenges. The “P-words” — preparation, people, prediction, and production point Read more
The Internet of Things (IoT) is rapidly emerging as a transformational paradigm with a multitude of products and services now available and being adopted by corporations as well as individuals seeking to harness the vast opportunities it offers. But we do face a major obstacle in realizing the full potential of the IoT. The sheer variety, volume and velocity of data generated by the IoT presents unprecedented challenges in deriving meaningful and actionable insights and calls for a strategic approach to data management and usage. These approaches also need to address business strategies, business processes, enterprise architecture, systems and applications, and security and privacy considerations. It is also important to examine and decide what data Read more
A good way to make predictions is to recognize current trends and then extrapolate them into the future. The longer the trends, the more confident you can be about the predictions. Thinking about software development processes, we see two long-term paths that software development has taken. These paths are the basis of both our joint prediction for the coming year and the kind of holistic consulting we will focus on in 2015. The path some have taken has been moving from one lifecycle process to another, each containing a set of prescribed practices. These, in rough order, are waterfall, spiral, controlled iteration/RUP, Xtreme Programing, Agile, and DevOps. We may have missed one or two, plus Read more
In his highly influential book, The Lean Startup, Eric Ries introduced term “minimal viable product” (MVP). As Ries rightly points out, firms putting out new products typically spend too much time and money on features that miss the mark somehow in meeting customer needs or are simply unnecessary. The result is a delayed over-expensive product that is more likely than not an economic failure. Reese proposes a better alternative: put out the least function (minimal) product that you can that might meet customer needs or at least will draw customer attention (viable). This way the team can test the market with different feature sets, get customer feedback, and commit development resources to the expensive activity Read more
As the Internet of Things (IoT) becomes a reality, the volume of data that will be generated by the multitude of connected devices, machines, and processes — in the consumer, business, and industrial worlds — is expected to be massive. In short, the more devices and machines that get connected, the more data that is going to be generated. Achieving some kind of business value from this massive data reservoir will require the use of big data storage and analysis technologies that can scale to meet the constantly increasing demands placed on organizations. These include: NoSQL file systems NoSQL databases High-performance relational analytic and in-memory database appliances Hybrid relational databases with embedded MapReduce Streaming analytics Read more