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Self-Service Analytics Use Cases

Self-service analytics offers dynamic reports to business users, who can analyze the data by sophisticated, in-built functions. This kind of user empowerment reduces reliance on IT staff. Moreover, self-service business intelligence (BI) capability may additionally equip users with external data access and built-in features to instantly generate finished reports. To use a complete range of […]

Blockchain Trends in 2020

2020 is likely the year when blockchain technologies will witness higher adoption rates and usage across industry niches. As announced in 2019, China may lead the way to substantial investment in blockchain research and applications. The largest cryptocurrency exchanges are in China, and this year may see some dramatic deployment shifts from the multi-cloud blockchains […]

Fundamentals of Cognitive Analytics

The journey of data analytics began with simple descriptive (review of past events) and diagnostic (analysis of past events) exercises and moved to the more sophisticated predictive and prescriptive genres,where advanced data models have enabled accurate future forecasts and actionable intelligence. And now cognitive computing has further strengthened the actionable predictive power of the machines […]

Hybrid Cloud vs. Multi-Cloud Architectures

The workloads (applications) running on an enterprise hybrid or multi-cloud network determine the architectural requirements. All cloud architectures share some common patterns, while the specifics of running workloads necessitate custom architectures. The architecture patterns are broadly of two types: “distributed-deployment” pattern and “redundant-deployment” pattern. In the former, an application runs in an environment best suited […]

Data Architecture and Data Science: What is the Intersection?

Data Science, in practice, should ultimately combine the best practices of information technology, analytics, and business. On the other hand, Data Architecture enables data scientists to analyze and share data throughout the enterprise for strategic decision-making. Thus, without a sound Data Architecture in place, data scientists will remain severely handicapped in their abilities to develop […]

Data Strategy vs. Business Strategy

For any transformational Business Strategy, data-driven intelligence must be “readily accessible, interpretable, and actionable” whenever necessary. At the macro level, a data-driven culture has to be consciously propagated throughout the organization, end-to-end. Digital businesses have acknowledged the importance of data accessibility and have embraced this culture within their business model to remain competitive. The late […]

Data Science Trends in 2020

The exponential growth of data, partly generated by sensor-driven devices, is making Data Science and machine learning (ML) market differentiators in global business-analytics solutions. With the rising demand in Data Science and ML skills, 2020 may well be a witness to several new trends in the field.  According to IDC: “[I]f our digital universe or […]

The Future of Deep Learning

Deep learning (DL) became an overnight “star” when a robot player beat a human player in the famed game of AlphaGo. Deep learning training and learning methods have been widely acknowledged for “humanizing” machines. Many of the advanced automation capabilities now found in enterprise AI platforms are due to the rapid growth of machine learning […]

Artificial Intelligence and Machine Learning Trends in 2020

“Artificial Intelligence and Machine Learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing, or application.” – Gartner An article on the future of AI and machine learning mentions that while cloud technology offers “agility to business processes,” artificial intelligence (AI) and machine learning (ML) technologies […]

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