SigmaWay Blog

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Data Science: Solution to Greek Crises?

It had been believed that Greece had struggled too much to meet the criteria for Euro entry. Official figures showing Greek deficit that were used to prove accession were found incorrect in 2004, and the authority continued to submit frequently revised statistics to the EU for the next decade. Data science could play a key role in protecting Greece. In 2011, Fact and Fiction in EU Governmental Economic Data (a research paper) used Benford’s Law up to a decade of economic data from 27 EU states. Benford’s Law states that in many naturally occurring collections of numbers the small digits occurs disproportionately often as leading significant digits. Benford’s Law was also used by financial auditors as a key to their fraud detection and the researchers tried to relate it to economic data. Researchers calculated the difference between the actual value and the expected value. After some research and analysis researchers found that Greece was the country with greatest deviation and they subject it to the effectiveness of Benford’s Law in determining the irregularities and manipulations in macroeconomic data. Now the question arises could data science and Benford’s Law let Greece to evade crises by keeping it away from Euro. The answer is no because the figures shown by Greece were hesitating. In fact it was Germany and France who broke the 3% budget deficit rule. Benford’s law might have helped, but the entry of Greece in Euro in fact was a political decision not economical. According to researchers, a little focus on Benford’s Law could help in recovering from such a devastating situation. Read more at: http://www.smartdatacollective.com/timoelliott/329137/could-data-science-have-saved-greece

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Coming soon: the age of predictive analytics

Predictive analytics tools and techniques are becoming a rage nowadays because of their immense application in a variety of sectors. Collecting data and predicting future trends have been so easy. More and more business are vying for these tools as they help with predictive modelling of customer behavior. Even bigger potentials are lurking in the near future and organizations are investing in the development of these software keeping that in mind. Companies which have still not adopted these software are falling behind in competition with other firms. Thus there has been a surge in the usage of predictive analytics as every firm is craving for more information. Read more at: http://www.dataversity.net/how-your-business-can-benefit-from-predictive-analytics/

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Self service analytics

Self-service analytics softwares are being used by businesses now and it has given rise to a new need, data governance plans. These new softwares provide a host of benefits. These have made accessing and analyzing data a lot easier coupled with the ability to feed bad data back into enterprises. A competition has been brewing between software vendors regarding improved data governance. Companies are launching business intelligence products that stress data governance. Such softwares can be built around the company's pre-existing enterprise data infrastructure bringing multiple data sources into a common data warehouse accessible by the entire organization. Read more at: http://www.dataversity.net/adding-data-governance-tools-to-self-service-analytics/

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Genomics: a new beginning

A startling revelation has been made by a group of math and computer experts that has been hard to digest. Leaving behind data consumption giants like you tube, twitter in social media and astronomy, particle physics in science the field that has emerged as a leader is genomics.  Genomics generate the most electronic bytes per year relative to other fields. It has been a challenge to capture, store and interpret the genome encoded biological information. Data generation has increased at a fast pace with the growth of biological sciences. Leading edge data generation and processing technologies are needed to tackle the present situation be it in the field of biological sciences or social media or high tech science. To know more, please follow: http://www.dataversity.net/wheres-the-biggest-big-data-to-be-found-genomics/

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Big Energy Savings with Big Data

The Energy industry is set to benefit largely from the usage of big data and analytics. Efficient use of information and improved analytics will help meet the difficult economic and environmental goals, bringing energy into the next century. For this we must update our energy infrastructure with the necessary software for collection and analysis of the required data. The potential of big data is such that it can help all customers support energy savings along with providing an environmental upside. Big data once employed correctly can improve operations for the benefit of businesses, customers and our environment. While the energy industry’s use of big data is future-focused, real progress is being made and these investments have improved operational efficiency and reduced the cost of energy all while helping protect the environment. Read more at: http://thehill.com/blogs/congress-blog/energy-environment/247559-big-data-means-big-energy-savings

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Open Source The New Trend

Most companies are deriving benefits from open source software's, as numbers of programmers and developers are provided access to the source code. This has helped employees gain domain expertise through collaboration. Open source brings higher visibility and better business opportunities. The reasons for growing prominence are:
1. Intellectual property concerns no more hindering the use of open source.
2. Enhancing reach and learning of the community by diversity of thought and better technique.
3. Providing better opportunities for interoperability between competing firms.
4. Increase analytics penetration.
5. Demonstrating technical ability, where ability to think innovatively can be measured by a potential customer.
To know more: 
http://bridgei2i.com/blog/why-open-source-is-important-to-analytics-industry/

 

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Big Data vs. Human Spirit

Big Data Analytics which is nowadays so useful in sports, also couldn't save England cricketers during their recent World Cup match against Bangladesh. The then coach of England, Peter Moore started believing in numbers more than the spirit of the cricketers. But a great-turnover came up over the team when they defeated New Zealand in a series of one-day match by 3-2. Both teams broke one-day records and entertained the English cricketing public like never before. This wasn't done by analysis of numbers but by abilities of cricketers. Thus, Big Data is all-time powerful but can never be more than what human spirit is. Same example goes for recruitment. Read more about this article by Matthew Reaney, Director and Founder (Big Cloud) at: https://channels.theinnovationenterprise.com/articles/big-data-and-the-human-spirit

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Internet of Extraordinary Things

Some of the unconventional ways in which Internet of Things (IoT) creates economic and social value are by detection of earthquakes in hospitals and alerting the administration for evacuating patients, reporting and assessing severity of car crashes and thus helping the victims to get help faster.
Certain examples that show how IoT is integral to several industries:
• The era of “Agriculture 3.0” was characterized by farmers whose decisions about what crop to plant and when and where to plant them was based on analysis of sensor data, weather data and other factors. This form of farming helps increase the yield in a cost and resource efficient manner.
• European airplane manufacturing company uses scanners In airplane assembly lines in order to send required information to robots who then finish the work accordingly.
• Internet of Things is used in Restaurant business for ensuring data-driven quality control.
With decreasing cost of connected devices, the scope of IoT will keep increasing in the future.
Read more at: http://www.smartdatacollective.com/joshua-new/329188/internet-ordinary-things-still-extraordinary

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Discovery Analytics: Hacking or R&D

There had been a misconception that discovery analytics is hacking. Every discovery process involves going through some data, analyzing it, making some conclusion. So why would some people judge it as Hacking? Highly prioritized business problems that occur in mind led to discovery process. After having some discussion the major component which addresses the problem is analytics. Analytics brings up the new ideas that could be solution to the business problems. One can have analytics as the strategic component of his business; just the requirement is that he has to invest in analytics like other components say core products and services that his company provides. Discovery analytics cannot be considered as hacking than any other research and development activities are. But truly speaking both of them are the same. The products sold in the market have to go through some background processes that are invisible to buyers. Huge investment, many trials and experiments are required to get a finished product. Discovery analytics are much similar to that. Not all attempts will give appropriate results, but if choosing the right doors it will result in high level of strategic value. Most of the people are familiar with R&D because it is viewed as rational, scientific, disciplined approach to developing new ideas and products. An analytics R&D function can be built just by letting few number of human and technology resources to address only a few critical business problems. When you get positive results, apply it to more number of problems. If every thing goes in right direction then we will get a stable and well functioning analytics research and development function. Read more at:http://www.smartdatacollective.com/billfranks/329559/discovery-analytics-it-s-not-hacking-it-s-rd

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Why is Efficient Data Management Required?

Data management has become the epicenter of success model for any organization. Human beings are generating huge amount of data everyday but most of the data is in unstructured form. The need to effectively manage data and create new flexible systems for effective integration of data across all databases is the need of the moment. Junk records, duplicate records and outdated records have only added to the costs of the organization and success for any organization will be how effectively its employees are able to create and manage the data on regular basis. The duty of cleaning up the data is often imposed on the IT department but they are just the gatekeepers and it is the employee who needs to take care of his or her data, be it a clerk, manager or even the CEO. To know more:

http://it.toolbox.com/blogs/insidecrm/why-is-data-so-difficult-to-control-68067

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Look beyond big data to get optimized

The amalgamation of big data and analytics isn't enough to deliver insights especially in the area of pricing and margin optimization. In this competitive world, every company strives to be better than the other and some have already gone ahead to boost sales and margins by using levers. Here are five important tips to ensure an improved pricing and margin optimization. They are:

  •  Increased focus on revenue management rather than on pricing and promotions.
  •  Hiring outstanding candidates and having a more effective organizational structure.
  •  Adopting decision based data management techniques.
  •  Choosing or designing tools using easy-to-use solutions that are understood by all.
  •  Having dedicated leaders who can drive all others team to achieve an insight-driven leadership.

Read more at: https://channels.theinnovationenterprise.com/articles/7715-it-takes-more-than-big-data-to-get-pricing-and-margin-optimisation-right-for-your-business

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Workforce analytics to ensure high retention rates

The success of a company is vested on its employees. It’s the employees who ensure that resources of the company are utilized to their full potential. But at times it becomes difficult to identify the best members of the staff. Workforce analytics comes into play here. Workforce analytics enables organizations to get a complete picture of their workforce and identify ways to improve it. It allows organizations to identify and retain their most important staff. Workforce analytics involves analyzing large sets of employee data to find correlations and patterns. Statistical techniques like tests of significance, factor analysis and multivariate analysis are applied and charts are produced to bring together all information available about a team. HR department can then leverage these insights to achieve high retention rates. Read more at: https://channels.theinnovationenterprise.com/articles/workforce-analytics-are-you-retaining-your-highest-performers

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Big Data for Hurricane Forecast

As researchers and scientists get access to the plethora of information of weather patterns, they are getting better equipped to deal with upcoming disasters. This data however is massive and highly complex thus the data gathering serves as only a part of the solution. Governments today are realizing the need for data-driven forecasting to keep up with the volume and variety of information required for smarter forecasting. Predicting weather anomalies more effectively could save thousands of lives during natural disasters. The process requires delivering more accurate forecasts and delivering them sooner. Data analysts use the voluminous data gathered to develop reliable forecasting models. Making sense of the data and building actionable intelligence will largely help protect the public from natural disasters. Read more at: http://www.forbes.com/sites/centurylink/2015/07/08/hurricane-forecasts-get-better-give-more-warning-thanks-to-big-data/

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Ease to Recruitment Forever, Thanks to Big Data

Evidences showed that recruitment have not been so easy during past years. Recruiting new employee requires a huge investment for most companies, specifically in managerial or professional role, which absorbs large proportion of company’s revenues. In the presence of big data, planning and strategies can improve recruitment process. US financial services company used big data analytics to examine the performance of employees. What they observed was that top performers were mostly those who had higher education. Office equipment manufacturer Xerox used analytics to study the performance and profile of candidates recruiting for its call centers which reduced the staff turnover of 20%. Big data is attracting employees and with the help of some tools such as Cornerstone and TalentBin (tools to crunch data) made it easier to find candidate for the right position. Online recruitment services are also enjoying the benefits of big data. Say for example it made easier to look at what are the areas of interest, average spending, experience, location of service. So, it is easier to plan ahead and prioritize. Read more at:

http://www.smartdatacollective.com/bernardmarr/327498/how-big-data-changing-recruitment-forever

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Big Data Challenges

Today, enterprises have come a long way dealing with the big data challenges. But there are more to go. Revisiting a few of them would help understand the task ahead. Timo Elliott, innovation Evangelist for SAP, in his blog Business Analytics talks extensively about the following 5 challenges:

• There’s still a lot of technology to learn

• The right people are still hard to find

• The right business case is key

• Integrating with existing systems is more important

• New business models are the next big opportunity

For an enriching account of each of them follow the link http://timoelliott.com/blog/2015/05/top-big-data-challenges-revisited.html

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Making Sense of Unstructured Customer Data

CRM systems are used in organizations all over the world to collect and maintain data about customers and prospects in a structured form. However, what about the huge amount of data that is present in vague formats before it is structured in CRM systems. "Content Intelligence" is a natural language processing system that extracts meaningful data from E-mails, reports, customer interaction meeting minutes and assigns metadata to the content for ease of access by the CRM system users. This reduces a lot of workload for them as they do not have to read through vast amounts of customer interaction data. For more visit:

http://it.toolbox.com/blogs/insidecrm/harnessing-unstructured-data-for-crm-68008

 

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Big Data can change your Business

Starting off as a small time entrepreneur it might be difficult to see the use of Big Data for your company’s growth. After all Big Data seems to be a term befitting multi million dollars firms, not for start-ups. In reality this isn’t true. Your small start-up can grow exponentially at a affordable cost using data resources which can be availed online by almost anyone.
Here are a couple of ways how it can work for you.
Customer Relationship Management (CRM):
A very important resource for any business is CRM software. Owners can set up a simple CRM spreadsheet, even if it’s just one single webpage, lets you to grab your customer’s feedback which helps towards your company’s growth.
Marketing:
As a small business owner you cannot afford to waste your valuable resources on a  misplaced advertisement or trying to market your product when there is no demand for it. You can use Big Data to analyze the market trends to key in on when and where buying habits are highest.
Big Data is everywhere and you can make use of it easily as long as you keep it simple & streamlined and not overdo it.

Read more at: http://www.smartdatacollective.com/keithtullyy/322521/how-small-business-can-use-big-data

 

 

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The Problem with Genomic Big Data

Our computational capabilities required to handle human genome data will rapidly exceed those of Twitter and YouTube. Computer scientists are realizing that they are not equipped with the growing flood of genomics. Almost 2 Billion human genomes would have been sequenced by the year 2025 according to a journal - PLoS Biology. The data-storage demands for such data could add up to around to 2-40 Exabyte (1 Exabyte is 1018 bytes).  The journal states that Genomic data would outstrip YouTube's projected annual storage needs of 1-2 Exabyte of video by 2025. Storage however would only be a small part of the problem. The computational requirements for acquisition, distribution and analysis of genomics data could be even more demanding. Genomics furthermore lack the standards for conversion of raw sequence data into processed data. Read more at: http://www.nature.com/news/genome-researchers-raise-alarm-over-big-data-1.17912

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Analytics Help CMOs To Innovate

Employment of analytics professionals into the marketing world goes far behind the usage of visualization techniques and data processing. Marketing enterprises are keen on hiring data and analytics professionals. It's a well-recognized fact that analytics not only help companies to take profitable decisions but also provides them with opportunities to build strong relationship with customers, increase sales volume etc.  Daniel Kehrar (VP Marketing, MarketShare) in his article on Forbes listed out the five ways in which brand marketers can innovate with analytics and they are as follows:

1. Use insights to enrich what you offer.

2. Perfect your programme.

3. Eliminate digital and channel silos.

4. Be predictive.

5. Merge brand measures with direct response.

Read more at: http://www.forbes.com/sites/forbesinsights/2015/06/29/5-ways-brand-marketers-can-innovate-with-analytics/

 

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IT Operations Analytics: Perfect Use case of “Big Data” Problem

ITOA or IT operations analytics is a recent entry to the field of analytics. ITOA automates the process of collecting, organizing, and identifying patterns in highly distributed, diverse and fast-changing service and application data to identify problems faster and improve IT system performance. IT Operations Analytics can be applied to the modern IT Infrastructure and Operations environment. What it exactly does is that it Collects, index and monitor logs and events for abnormalities, perform ad-hoc searches of all log data across the entire IT environment from a single console and correlate log data with events and service models, or application groups. This helps in detecting and resolving service issues more quickly than ever before. Read more at: http://insidebigdata.com/2015/06/09/it-operations-analytics/

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