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Big data systems help companies build new business strategies
This article is part of the Business Information issue of October 2017, Vol. 5, No. 5
Big data systems, for some companies, aren't just platforms for new types of data processing and analytics applications -- they're the driving force behind entirely new business strategies. That's the case at iPass Inc., which is using a big data environment to fuel a strategic shift from pay-for-use Wi-Fi access to tools for managing and optimizing mobile connectivity for corporate users. Introduced in late 2015, the company's iPass SmartConnect software includes algorithms that identify Wi-Fi access points and rank them on performance so mobile users can connect to the fastest and most reliable hotspots available. That marks a big change from when iPass gave users a static list of hotspots. And it wouldn't be possible without the underlying data management platform built around the Spark processing engine, said Tomasz Magdanski, director of big data and analytics at iPass. "We do need the big data architecture, 100%," he explained. "There's no way we could crunch all this data in real time and do all the ranking and ...
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Features in this issue
Organizations hungry for more revenue are using Hadoop and other big data technologies to break their existing business molds and pursue new strategies and product offerings.
Getting real-time information on where goods are in a supply chain is commonplace with sensors and big data, but some firms use machine learning to predict more accurate ETAs.
When Swisscom needed to merge two SAP ERP systems and several SAP BW data warehouses, it upgraded to one SAP BW on HANA system to reduce data from 5 TB to 1 TB.
Unsung and unheralded, semantic technology is a key component in artificial intelligence and other big data applications. Yet, like AI, it still faces hurdles to going mainstream.
Columns in this issue
Companies are using big data systems, deep learning and machine learning techniques to drive software advances. To go even further, their data management systems must also evolve.
Big data often comes with big data management problems. Clean, well-defined metadata can make the difference in analyzing big data and delivering actionable business intelligence.
Businesses spend millions of dollars to collect, mine, prep and analyze data to gain an edge in the marketplace. Yet, they have a hard time determining big data's actual value.