SigmaWay Blog

There are significant opportunities to make use of big data techniques. Unlike technology and consumer retail sectors in which advanced analytics has been implemented, it can also be used in other industries like insurance, health care, banking and public sector. In insurance, data can be aggregated from public sources and specialist data providers, allowing companies to better target customers and frame policies accordingly. Banks are increasingly using big data to generate a much deeper view of their customers, combining the information collected from all of customer's interactions with bank with selective third-party data like paying patterns for mobile phone bills, tracking trends on social media platforms such as Twitter. Read more about this aspect in Dominic Barton (global managing director at McKinsey & Co.)'s article link:http://blogs.wsj.com/experts/2014/03/28/sectors-where-big-data-could-make-an-impact/?KEYWORDS=analytics 

Today, companies have the option of collecting information about consumers which was never available in the past. This information is collected through internal sources, such as company websites and sales records, and external ones, such as social media, smartphones and tablets. This vast amount of information on consumers is increasingly referred to as big data. When a consumer visits a website for the first time, cookies are sometimes uploaded on his browser containing a unique ID, making it possible for the company to identify him during his next visits. Once identified, it will be possible to link the consumer to all information the company stored about his profile, which makes personalized marketing possible. Today, because of prescriptive analytics models embedded into their operational systems, websites and apps can analyze consumer information in real time in order to offer personalized travel options instantly. In the next few years, we will witness a gradual move to 1-to-1 marketing in the online travel category, with each consumer treated in a different way in terms of the whole marketing mix. To know more about this visit:

http://blog.euromonitor.com/2014/05/big-data-unique-ids-and-prescriptive-analytics-revolutionising-online-travel-marketing-part-1.html  .

Today's big data and analytics efforts bring welcome relief to banks, insurance companies, healthcare agencies, non-profits, and other organizations that have habitually struggled with finding the most profitable customers and then selling to them. A new set of analytics reports can move these companies forward in connecting with their best customers. According to a research by Fractal Analytics, banking users are struggling in an industry where 40% of cardholders are inactive and 60% are unprofitable. Banks want to increase spending in its existing credit cardholder base, so that it can implement customer analytics framework that was once targeted at improving first-hand understanding of these customers' needs. Once the bank understood who its most profitable customers were, it developed a "genomic" understanding of how these customers spent their money and found that insurance and food expenses were among the leading "spend" categories. This enabled banks to plan and target promotions built around these major spend areas. By doing so, banks increased its value per customer while decreasing expenses on marketing campaigns, likely because the campaigns were better targeted. To know more about this go to: http://www.techrepublic.com/article/genomic-analytics-build-sales-by-finding-your-most-profitable-customers/ .

The supply chain is a great place to use analytical tools to look for competitive advantage, because of its complex nature and also because of the prominent role supply chain plays in a company's cost structure and profitability. Data analytics is the science of examining raw data and drawing conclusions about information. It is used by many business houses to facilitate better business decisions and verify or disprove existing models or theories. Relying on traditional supply chain execution systems is becoming increasingly more difficult, with a mix of global operating systems, pricing pressure and increasing customer expectations. There are also recent economic impacts such as rising fuel costs, global recession, supplier bases that have shrunk or moved off shore, as well as increased competition from low cost outsourcers. All these challenges potentially create waste in the supply chain that is where data analytics steps in. To know more about the role of data analytics in supply chain visit:http://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important .

In recent times, the quickest and the easiest way to reach out to the huge market is through paid search marketing like advertising on Google AdWords or through other engines. Research shows that almost 75% of the North American population remain online. Marketing Analytics allows you to monitor campaigns and their respective outcomes, enabling each dollar to be spent as effectively as possible. According to a study in 2008 by the Lenskold Group "companies making improvements in their measurement and ROI capabilities were more likely to report outgrowing competitors and a higher level of effectiveness and efficiency in their marketing". In search marketing, one of the most powerful marketing performance metrics comes in the form of keywords. It is the keyword data contained within each click which can be utilized to inform and optimize business processes, monitor industry trends, provide customer support and identify the product design. A successful online marketing strategy relies on a winning AdWords campaign. The strength of your AdWords campaigns will dictate how well you rank in Google; without a decent ranking, your site will never be seen by prospective clients. As was published by E-Consultancy Research, it's generally well known that "a paid search campaign will add prestige and credibility to an organization. To know more about marketing analytics go to: http://www.wordstream.com/marketing-analytics .

Fraudsters are more competent, better made, and creatively excellent than whatever possible time in the later past. Their adulteration arrangements include complex frameworks of individuals, records, and events. The evidence for these schemes may exist on multiple systems, incorporate various data sorts, and deliberately represent hidden activity. So an analyst has abundant investigative focuses on these frameworks with no true approach to join data or results. To prevent and uncover deception, one needs a solution that is more exceptional and advanced than hoaxers. A basic venture in fraud detection analytics is visualizing the patterns in your data between people, places, frameworks, and events. These data mining and profound analysis capabilities provide more context and better information, enabling more accurate data segmentation and data labelling, which further improves pattern recognition. To read more about it: http://www.21ct.com/solutions/fraud-detection-analytics/.

Sampling error can cause problems if they are not taken care of. Errors in judgment about sample size can be fixed easily and sample sizes must be considered seriously if big data is being used for predictive analysis. A leader trying to use big data in predictive analysis should always consult the data scientist. The way to understand whether enough data has been collected or not for the purpose of prediction involves understanding the tolerance of the risk associated to accept the assumptions drawn from the sample size characteristics. There are two types of risk: the risk that you're going to take some action when you shouldn't and the risk that you are not going to take some action when you should. Also enough information should be available about the sample variation and precision of measurement to know whether enough data has been collected to make prediction. To know more about importance of sample size in predictive analytics, go to John Weathington (President and CEO of Excellent Management Systems, Inc.)'s link: http://www.techrepublic.com/blog/big-data-analytics/why-samples-sizes-are-key-to-predictive-data-analytics/ 

This article elaborates on the sentiment analysis from tweets using data mining techniques. Instead of using SQL, it shows how to conduct such analysis using a more sophisticated software called RapidMiner. It explains how one can extract Twitter data into Google Docs spread sheet and then transfer it into a local environment utilizing two different methods. The emphasis is on how to amass a decent pool of tweets in two different ways using a service called Zapier, Google Docs and a tool called GDocBackUpCMD, along with SSIS and a little bit of C#. Zapier is used to extract Twitter feeds into Google Docs spread sheet and then copy the data across to local environment to mine it for sentiment trends. Next, it is shown how this data can be analyzed for sentiments i.e. whether a concrete Twitter feed can be considered as negative or positive. For this purpose, RapidMiner as well as two separate data sets of already pre-relegated tweets for model learning and Microsoft SQL Server for some data polishing and storage engine. Read more at:http://bicortex.com/twitter-sentiment-analysis-mining-twitter-data-using-rapidminer-part-1/

Insight, a free healthcare analytics software tool launched by Practice Fusion uses real time data from healthcare industry to show patterns against various diagnoses and prescriptions against diseases across seasonality, age, gender and other parameters.

Membership can be taken where more details such as patient and doctor details etc. are available. This software can also be useful for pharmaceutical companies to change their strategies. To know more kindly visit:

http://www.informationweek.com/healthcare/analytics/practice-fusion-releases-free-healthcare-analytics-tool/d/d-id/1268917

With the advent of healthcare industry, the flow of data has increased by leaps and bounds. Now with the presence of analytics, huge number of unstructured data can be easily analysed to find out patterns and behaviours which in turn helps the companies associated with healthcare to take more sound and logical decisions.

To know more kindly visit:-

http://www.healthcareitnews.com/news/healthcare-data-goes-big-great

While taking decisions on buying and selling in the bull market, very few follow the various technical indicators that are available with any charting software. These are some vital signals which people choose to ignore while making decisions on the market. But, if statistics are to be believed they are helpful in making profitable decisions. To know more kindly visit:-

http://www.forbes.com/sites/greatspeculations/2014/05/05/taking-the-technical-vital-signs-of-an-aging-bull-market/

Recently, Tibco made an announcement to acquire Jaspersoft for some $185 million and D&B announced that it has acquired small analytics startup Indicee. This shows that companies in order to be more focused and remain valuable to customers, it is very important to provide more value through insights from big data. Please go through the link for more details: http://www.forbes.com/sites/benkepes/2014/04/30/suddenly-everyone-wants-to-be-in-cloud-analytics/

The way technology is making a progress and competition is becoming tougher with increased uncertainty, big data and analytics tools have become important to your company. There is another matter that is also important - your customers. So, which will you give more importance? Your analytics tools or your customers? It is of no doubt that big data and analytics tools will give you hidden information that is not visible easily, by sifting through customer data. But, you have to remember one thing - analytics tools have no brains. It will never ever answer 'why' - well, that is the biggest answer for your business. The reason - analytics tools never understand your customers!

To attract customers to your shop, or to your website, you have to build an experience within them. Your marketing communication strategies will form that experience and reshape them. You have to address questions like what your customers want and why they want - in short, you have to understand their behavior. So, to excel in business, it is more important to understand your customers, not analytics tools.

How to understand your customers' behavior? Read them at: http://thenextweb.com/entrepreneur/2014/05/21/beyond-analytics-understanding-humans-scaling-business/ .

For emerging markets, exploring data to predict trends is not an easy option, mostly because of less availability of data in new fields. However, organizations in the emerging markets have the option of gradual progress. They have to start with analysing small data and then there will be scope to move into big data in near future. Problems for companies trying to do business in these areas are limited access to information and appropriate analytic modelling techniques. Gartner reports that companies are predicting 40 to 60% of their growth in revenues will come from emerging markets over the next decade, and McKinsey & Company predicts that in 12 years, 57% of the nearly one billion households with earnings greater than $20,000 a year will live in the developing world. "Companies need analytics to cope with these new markets," said Richard Howells, vice president of Go to Market for SAP. To know about this aspect, please visit the following link: http://www.techrepublic.com/article/start-with-small-data-in-emerging-markets-to-get-to-big-data-analytics/#. 

When it comes to businesses and increasing their profitability, it is of no doubt that Big Data has brought in revolutionary changes. With proper handling of Big Data and data management, companies are trying to increase customer satisfaction and increase customer retention. Now, let's take a different look. 

Consider trading - capital market is one industry, where millions and millions of data float around. Regulatory bodies, banks, financial institutions store and analyze all these data that range over a large time horizon. They also need to study risk management practices and create new trading strategies. In capital market where focus has shifted from high frequency trading to discovering patterns and insights from financial data that can be used as case studies, big data can be made to its use. Financial services organizations are needed to invest in data management software that can harness the power of big data technology and extract hidden information.

How can they do so? Read them at: http://www.bankingtech.com/221932/big-data-and-data-management-in-capital-markets/ .