Clarifying Data Analytics Concepts for Industrial Engineering

Challenges from Industrial Data Analytics

Big data applications in industry pose a number of unique challenges, setting them apart from domains such as consumer analytics in the web. Central for many industrial applications is time series data generated by often hundreds or thousands of sensors at a high rate, e.g. by a turbine. Another important data source are log files generated by control units in complex technical equipment, e.g. ...

Industrial Engineering: Concepts, Methodologies, Tools and Applications

A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection

Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....

Data Warehousing and Analytics in Banking: Concepts

In an increasingly competitive market, banks are constantly searching for sustainable competitive advantage to help them maintain their edge against competition. Over the years, banks have tried various drivers for competitive advantage, none of which were sufficient barriers for competitors. Understanding the behavior of their customers and using this knowledge to drive the interaction with cu...

Current Concepts in Scaffolding for Bone Tissue Engineering

Bone disorders are of significant worry due to their increased prevalence in the median age. Scaffold-based bonetissue engineering holds great promise for the future of osseous defects therapies. Porous composite materials andfunctional coatings for metallic implants have been introduced in next generation of orthopedic medicine for tissueengineering. While osteoconductive materials such as hyd...