SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

How to Achieve Organizational Agility

 

If the country is changing faster than the expectations, then organizations are faced with the challenge of moving with those changes. It is affected by fast evolving markets, ever changing technology, increasing competition and changing preference. So how to react to these changes? First is by gathering intelligence, using big data analytics to discover patterns by tracking commercial data, for example in consumer spending, movements of competitors. Next is to look for the unexpected. This involves constantly improving your business model, inculcating the changes that raise inside and outside the industry. Read more at: http://www.forbes.com/sites/bensimpfendorfer/2015/07/07/the-agility-factor-in-asias-competitive-markets/

 

 

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Unified Analytics: An Insight

Nowadays, companies are focusing on the best possible answers than asking the right questions to get the minutest details. To get the best details, a set of connect questions has to be answered which requires using a connected set of data sources. This is called unified analytics. It will enable the access and analysis of data from multiple sources on a single interface. But we need to keep certain things in mind like integration of unstructured and structured data which is not an easy process. Also, we need to look beyond traditional sources within firewall and focus the data strategy on customers. Read more at: 

 

 http://www.analytics-magazine.org/web-first/1266-unified-analytics-a-new-mastery-over-the-data-wave

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Investment banks recruit for rise of big data analytics

The investment banks are now looking at how they can use big data to do what they do better, faster and more efficiently. Senior executives at the banks want to enhance how they use data to raise profitability, map out markets and company-wide exposures, and ultimately win more deals. Big data is also a fundamental element of risk-profiling for the banks, enabling data analysts to immediately assess the impact of the escalation in geopolitical risk on portfolios and their exposure to specific markets and asset classes. Specifically, banks have now built systems that will map out market-shaping past events in order to identify future patterns. There lies the requirement of big data talent!

The banks are actively recruiting big data and analytics specialists to fill two main, but significantly different roles: big data engineers and data scientists. Data Scientists are responsible for bridging the gap between data analytics and business decision-making, capable of translating complex data into key strategy insight, while Data Engineers typically come from a strong IT development or coding background and are responsible for designing data platforms and applications. The competition between banks and fund managers to hire big data specialists is heating up. Data scientists are expected to have sharp technical and quantitative skills. They are in highest demand and this is where the biggest skill shortage exists.

To read more, visit the link given below:

http://www.computerweekly.com/opinion/Investment-banks-recruit-for-the-rise-of-big-data-analytics

 

 

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Red Hat's Big Data strategy: A full stack approach

Open source software and infrastructure provider Red Hat announced its Big Data strategy. To know about big data strategy in details, go through the article by Andrew J. Brust, entrepreneur and CTO, specializing in application development, databases and business intelligence technology.

http://www.zdnet.com/red-hats-big-data-strategy-a-full-stack-approach-7000011574/

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