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Data Modeling in the Machine Learning Era

Machine learning (ML) is empowering average business users with superior, automated tools to apply their domain knowledge to predictive analytics or customer profiling. The article What is Automated Machine Learning (AutoML)? discusses a prediction that by 2020, augmented analytics capabilities will play a key role and be a “dominant driver” in the growth (and purchase) […]

Fundamentals of Data Virtualization

An innovative Data Strategy called “data virtualization” (DV) is employed to tackle high volumes data from varied sources. Data virtualization is widely used in enterprise resource planning (ERP), customer relationship management (CRM), and sales force automation (SFA) systems to collect and aggregate multi-source data. From multi-sourced data acquisition to advanced analytics, this technology seems to […]

Fundamentals of Self-Service Machine Learning

The recent organizational push for self-service Business Intelligence has helped the next challenge for business users become an increasing need. How to tackle the issue of having Machine Learning (ML) models embedded in all major analytics platforms? On the one hand, embedded models offer greater freedom and control over data analysis; on the other hand, […]

Prescriptive Analytics Use Cases

The term “prescriptive analytics” denotes the use of many different disciplines such as AI, mathematics, analytics, or simulations to advise the user whether to act, and what course of action to take. In that sense, prescriptive analytics offers an advisory function regarding the future, rather than simply “predicting” what is about to happen. This newer […]

Data Governance vs. Blockchain

Data Governance is the hot topic in today’s security- and privacy-concerned digital ecosystem. Blockchain technology offers data-centered security to sensitive, transactional systems that require tamper-resistant, fully auditable tracking mechanisms. Thus, blockchain and Data Governance (DG) complement each other in many ways, while maintaining distinct operational philosophies and application turfs. Blockchain is today’s preferred technology for […]

Implementing a Cloud Data Strategy

At a time when most major companies are showing a long-range commitment to “data-driven culture,” data is considered the most prized asset. An Enterprise Data Strategy, along with aligned technology and business goals, can significantly contribute to the core performance metrics of a business. The underlying principles of an Enterprise Data Strategy comprise a multi-step […]

The Digital Mesh: How is it Changing Enterprises?

Is this a science fiction movie? No, The Digital Mesh — the long-awaited gift of connected technologies — is here now. Advanced science and telecommunications technologies together triggered the latest technology disruption, enabling people, processes, and digital devices to engage in a way that is vital for the survival of modern businesses. Landmark Digital Disruption: […]

Data Architect vs. Data Engineer

The data architect and data engineer work in tandem – conceptualizing, visualizing, and then building an Enterprise Data Management Framework. The data architect visualizes the complete framework and creates the blueprint, which the data engineer uses to build the “digital framework.” The data engineering role has recently evolved from the traditional software-engineering field. Recent Enterprise […]

Data Modeling Trends in 2019

IT technologies are rapidly changing our lives. Whether it’s your daily grocery purchase, monthly bill payments, booking railway tickets, or receiving online healthcare consultation, data technologies have penetrated every business model, large, medium, or small. Recent cloud platforms, coupled with Big Data and IoT technologies, have ushered in a new era of “smart technologies” powered […]

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