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Data Governance and Data Quality Use Cases

Given the high volume of erroneous data floating across the enterprise, it is increasingly difficult for industry operators to make business decisions or plan any course of action based on such poor-quality data. Moreover, what’s the point of applying advanced analytics or BI technologies on data that is flawed? A whitepaper titled Getting Ahead of […]

Impact of Data Quality on Big Data Management

As the available industry literature suggests, Data Quality (DQ) is seriously hindering the success of many Big Data projects. However, it is apparent that without an organized movement in favor of Data Quality for Big Data, nothing will actually happen to change the current scenario. In an interview with the CEO of Informatica, Anil Chakravarthy, […]

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 […]

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