SigmaWay Blog

Sales and marketing platforms can easily be combined to generate a closed-loop approach to marketing analytics whereas business analytics understands the structure of the past to estimate what might happen in the future. Through marketing analytics, marketers can easily measure all aspects of their marketing efforts. Business Analytics can measure everything from warehouse efficiency and manufacturing. Business Analytics typically incorporate high level data from each department to gain knowledge of how the organization works. What makes marketing analytics different from other business analytics, is its concentration on real market output. Marketing analytics go beyond measuring strictly online performance and provide representatives from sales, customer service and senior business management with real market feedback that helps guide decisions on where to invest and how to prioritize. Thus marketing and business analytics are really a two way street - without marketing data business analytics wouldn't tell the whole tale, and vice versa. Read more at: 

http://blog.hubspot.com/insiders/marketing-analytics-vs-business-analytics

When one starts a new project that involves analyzing his company's data especially when the data is stored across functional areas, that person is in trouble. The data lake model helps in this case. To get access to data doesn't require an integration effort, because data is already there in the lake and one can apply MapReduce and other algorithms to use it. In the lake some data are unstructured or not structured by us for a given project. To construct a data lake one needs to learn some of the Hadoop stack such as Sqoop, Oozie and Flume. Next a data scientist should be found who understands Hadoop as well as business and the company’s business data in particular. Then one should start with basic cases and use simple and familiar tools like Tableau to make nice charts, graphics, and reports demonstrating that he can do something useful with the data. Next security up front should be considered, as well as who can access what data. Use of core Hadoop platform is beneficial. Apart from this one should keep in mind that lake security may have business unit implications and one should not have a lot of mini lakes i.e. data ponds that are separate and not equal. Read more at:http://www.infoworld.com/d/application-development/how-create-data-lake-fun-and-profit-246874?page=0,0

Nowadays a new set of tools is developed to help business users visualize data and interact with it in real time. One may think of mobile reporting as a good device for business but it is not good enough indeed and we need analytics tools too. Mobile analytics can be quite different from traditional business intelligence, in fact, and may even change the way you work with data comfortably behind the desk. Three basic aspects of mobile analytics are- For any application, the touch interface makes the difference between mobile and desktop environments. It encourages exploration. It is possible to make interactive areas large enough to touch through a mobile device. Mobile analytics also demands responsive interface design and the analysis must work across many devices. A responsive interface supports many form factors and one’s BI platform if designed for mobile ought to handle these scenarios generically. Mobile analytics also helps in speedy discovery and facilitates an interactive experience which is touch-enabled. These practices not only enable, but encourage exploration.

Read more at:http://www.infoworld.com/t/business-intelligence/getting-your-hands-data-mobile-analytics-246331?page=0,0

One can use the big data, available in hand, in a right or a wrong way. Here is the list of top 10 worst big data practices which one should try to avoid. First, though MongoDB has an aggregation platform, it is not good as an analytical system and thus should not be used as big data platform. Second, RDBMS schema is used as files by many which should be avoided too. Third, creating a series of data points. Fourth, failing to develop use cases. Fifth, over-dependence on Hive should be reduced as the whole point of big data is to expand beyond what one could do with one technology. Sixth, it's not right to treat HBase like an RDBMS. Seventh, trying to install Hadoop and all its moving parts on 100 nodes by hands is also a worst practice. Eighth, one should also avoid RAID/LVM/SAN/VM-ing one's data nodes. Ninth, instead of treating HDFS as just a file system one needs to think about how one is going to secure all of this and for whom. Finally, everyone is free but each one should have a plan. Read more at:http://analytics.theiegroup.com/article/53c925453723a81857000073/The-10-Worst-Big-Data-Practices-

Massive amount of climate data waits to be  interpreted by the press, public agencies, and general public and the challenge lies in finding analytics software that is easy to use, and produces understandable results, and can handle the volumes of big data available. However, to get a handle on the sort of governmental data on climate and resources that often resides in generic comma-delimited files, Circle of Blue, who specializes in reports on the global competition for water, food, energy in a changing climate, uses QlikView Business Discovery Platform. Such visual analysis software helps users to view, explore, and interpret the data with little technical training. Circle of Blue hopes to make the public more informed about the vulnerability of water supplies in the era of climate change by merging technology with on-the-ground reporting and online networks. With the use of Qlik View platform, it becomes easier for them to deliver data to a wide range of people. QlikView dashboards work with the large data sets to produce sophisticated, engaging, and state-of-the-art graphics. The data can be scaled to compare local information with national and global trends and that information, in turn, can help in formming public policy discussions.

Read more at:http://tdwi.org/Articles/2014/07/08/Massive-Climate-Data-Awaits-Analysis.aspx?Page=1

A Survey, based on the responses from 111 data scientists in US, found that Hadoop is too slow according to 76% of data scientists as they believe that the open source software framework requires too much effort to program and isn't fast enough to keep up with big data demands. On the other hand almost 91% of the survey respondents claim that they are performing complex analysis of data on the basis of which 39% of overall respondents say that their job is getting tougher. However, Big Data is becoming highly important for all enterprises. According to a research commissioned by Dell and conducted by Competitive Edge Research, a big section of midmarket companies with 2,000 to 5,000 employees are embracing the rise of big data and almost 80% percent of the midmarket thinks they need to better analyze their data, as they believe big data initiatives provide a significant boost to company decision making. Read more at:http://analytics.theiegroup.com/article/53baa9d23723a81e1300007b/Survey-Finds-Hadoop-Is-Too-Slow-Big-Data-Is-Too-Complex

The healthcare analytics market is expected to grow at a CAGR of more than 25% over the forecast period 2014-2019. Increasing healthcare IT adoption, centralized healthcare mandates across the globe, emerging fields of predictive, prescriptive analysis and venture capital are the factors driving the market growth. Digitization of world commerce, the emergence of Big Data and increase in the number of advanced technologies are other growth providing factors. Factors hampering the growth of the healthcare analytics market include lack of skilled labor with analytical skills, data securing and patient data privacy. North America holds the largest share of healthcare analytics market driven by US centralized healthcare mandates such as Meaningful Use and The Patient Protection & Affordable Care Act (PPACA). These initiatives assist to improve the acceptance of Electronic Health Records and Healthcare Information Exchange, thus improving the usage of analytics to influence the generated data. Read more at:

http://www.fortmilltimes.com/2014/07/21/3616557/research-and-markets-healthcare.html

Big data has a vital application in healthcare industry. Social media will increase communication between providers, patients and communities. This will not only work to globalize and democratize healthcare, but it is also a potentially important source of big data.  It will impact how these players engage with the healthcare ecosystem, especially when globalization, external data, regionalization, mobility and social networking are involved. The problem in healthcare isn't the lack of data but the lack of information that can be used to support decision-making, planning and strategy. In healthcare, big data challenges are compounded by the fragmentation and dispersion of data among the various stakeholders, including payers, data vendors, standards organizations, providers, labs, ancillary vendors, financial institutions and regulatory agencies. The entire healthcare system can realize benefits from democratizing big data access. Big data can make decision support simpler, faster and ultimately more accurate because rational decisions are based on higher volumes of data that are more current and relevant. Read more at:

Internet forecaster Mary Meeker in her latest report includes that trading of sensors for phones, tablets, etc., have increased by 32 percent up to 8 billion in 2013. And mobile data traffic is rising at an annual rate of 81 percent. With the change from desktop to all things mobile, high-thinking marketers should be looking for ways to make use of all the untapped signals available to them. Marketers can carry the opportunity to discard a huge amount of deadweight from their activities by:

• Sourcing new leads.

• Leveraging predictive lead scoring.

• Continuously personalizing.

The digital universe of data is growing largely and expected to reach 13 zettabytes by 2016. While out of 34 percent of the useful created data only 1 percent is being analyzed today. Today, companies must be thinking about gathering data and partnering with experts that have the machine learning capacity needed to enable truly data-driven marketing decisions.

  Read more at: 

http://www.destinationcrm.com/Articles/Web-Exclusives/Viewpoints/The-Impact-of-the-Mobile-Boom-on-Data-Driven-Marketing-97796.aspx

Big Data is a buzzing concept nowadays. When all people around the world are reviewing, commenting, tweeting, blogging, clicking pictures all about the same movie over the Internet, it makes a data worth billions of bytes. This data spread across the Internet is called the Big Data. According to McKinsey a business using Big Data to the full could increase its operating margin by more than 60 percent. Internet has provided businesses with new and profound ways to improve productivity. Companies will benefit from Big Data if they are able to extract unknown patterns from the data and use them in remodeling business activities. According to Weatherhead  University Professor Gray King, there is a Big Data revolution which is the fact that now we can do something with the data. As Gary King said “The importance of Big Data lies in improved statistical and computational methods, not in the exponential growth of storage or even computational capacity”. Read more at:

http://www.informationweek.in/informationweek/perspective/297095/unmasking-gold-internet

In the mid-1980s some of the big companies were trying to bring video telephone technology in the market but it was a big flop with the consumers. The market did not want video phones even though the technology existed. Today's banks have something at their disposal that the telecoms of the 1980s did not: big data and pervasive computing. The financial services industry is trying to create personalized banking so that it would use the right IT solutions and it would allow for robust predictive analytics- in order to use the banking features that will satisfy their customers and improve the bottom-line. The challenge is to understand how to have their data at their disposal into value. Stepping outside traditional platforms will help banks realize that they need to reevaluate self-service and customer engagement in this completely new environment. Banks need to make sure that they have a strategy around all self-service devices. Customers are ready to connect to banks over smart phones and tablets, from any location and at any time. For that to happen banks must use their customer feedbacks. Read more at:

http://www.informationweek.in/informationweek/news-analysis/297141/master-branch-online-platform-transformation

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Both data collection and use of social media API can help  the business in making elegant marketing imminent. An API is a program interface used by hunt engine optimization specialist to assess and arrest vital data applicable and hence improves their marketing strategies in the digital industry. As an application, the API helps digital marketers form their own web requests that will be well-suited to a certain website that will let for the faultless flow of data collection on these sites. A social media API permits commerce to simply collect social data across the social sites.Read more at:

http://www.socialmediatoday.com/content/data-collection-strategy-expand-digital-marketing-insights

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Social analytics is now well thought-out to be an element of trade aptitude approach where statistical data is composed, analyzed and utilized in anticipating consumer behavior. The logical consequences impending from the social data used help business to turn into more approachable to the altering desires of their clients and market industry trend. It is also employ by online shoppers to analyze and examine the marketing strategies of their competitors. The exercise of analytics has happen to be an important instrument for businesses in accepting the collection of significant data that is obtainable to progress their market competition. Analyzing shared data can be very difficult when made physically. Use of an analytics tool can make the progression smarter, organized and can arrest main metrics that would be hard through human involvement. The Google Analytics is the accepted tool used by online marketers in calculating social metrics and signals.

. Read more at:

http://www.socialmediatoday.com/content/analytics-strategies-measure-social-signals

Today, with the rise of mobile devices and simple health trackers, people will soon be able to analyze their own health data themselves. The proliferation of mobile devices has helped liberate the insights from that huge amount of data organizations are collecting. For years, big data and analytics has been the solitary domain of the enterprise and today there is no shortage of people in analytics space, from traditional enterprise players such as Oracle, IBM, SAP Business Objects, to relative newcomers such as Roambi, Tableau, and Pentaho. While businesses are analyzing big data to make decisions, individuals will soon be able to analyze big data to improve their own lives. Consumer can also choose which fitness band to use to check calories, number of steps, activity level, heart rate, sleep patterns, and so on. With this type of data collection, real time biometrics could help in reaching out alerts to doctor so that it can save lives. New innovations will allow individuals to compare their health metrics to others in similar demographics. Thus, analytics along with the interconnection between mobile device, wearable devices and appliances, we will soon have access to greater insights to improving our health.

Read more at:http://analytics.theiegroup.com/article/53a7f76e3723a85c3a0000a1/The-Health-Tech-Revolution-Will-Turn-All-Of-Us-Into-Big-Data-Wonks

In spite of being important, big data analytics is yet to be deployed successfully by most of the organizations. Many companies are struggling with how to maximize big data, and properly incorporate the results into something substantial. Results of the survey showed that the investment in analytics was growing rapidly. 64.4 percent of those surveyed said that their firm is investing more in analytics. However, just 12.6 percent of respondents said their company has completed several big data projects. One reason that prevents organizations from moving forward despite understanding the benefits of big data analytics, is the shortage of expertise in the field and with such lack of big data skills organizations are reluctant to take the plunge. It is also a major concern to keep sensitive information from the gathered big data, secured. On the basis of Big data analytics businesses should conduct their own research and see what options best fit their needs. However, technological innovation should be pursued to make big data analytics accessible to ordinary business users as without such innovation business could be left behind. Read more at:http://analytics.theiegroup.com/article/53a04cf93723a81d72000021/Is-Big-Data-Just-A-Big-Problem

The impact of big data in health care is tremendous and it has potential impact on every person as well. It helps in the advancement of disease diagnosis and treatment. Big Data is able to determine whether men need to undergo prostate cancer surgery or not, also can assess the risk of heart disease later in life, based on our health status as teenagers. Genomics, the genetic information, aims to discover the basis of heritable traits and understand how genes work to prevent disease and we may soon be able to see Web-based patient profiles that aggregate genomic data with other types of Big Data and produce "risk map" mobile apps that people can download to a smartphone. If it is about the hospital treatment, then also comes the importance of big data which requires the integration of information including admissions, records, nursing, diagnostic imaging, rehabilitation and home care. Researchers around the world are investigating ways to access, analyze and apply Big Data in healthcare. Corporations are looking for ways to use it to support their product development. Moreover, regardless of whether it's how patients are treated in the hospital or how they keep themselves healthy at home, they are learning about, interacting with and embracing Big Data .

Read more at:http://analytics.theiegroup.com/article/53a31b043723a81ea9000096/Making-It-Personal-Why-Everyone-Should-Care-About-Big-Data

One of the most promising trends in IT is the use of data to deliver to individuals- the decade old promise of personalization, which includes delivering the individuals the exact product and services as and when they need them. Nowadays we have a rapidly growing number of choices. Companies and other providers can help us sort these choices by analyzing data on our personal tastes and circumstances combined with analysis of mass data. Personalization increases the prospect of customer loyalty. The time lag between product innovation and commoditization has become shorter.  It establishes a more personal and binding relationship with customers. There are of course dangers. Companies and other data manipulators can use information to harm and some of the information they are gathering is highly private. Although individuals are concerned about their privacy, they are willing to share the most intimate data, if they think that doing so will improve their lives. Many problems need to be sorted out before data driven personalization becomes the norm, but the long term impact of this trend will be better products and services for individuals. Read more at:

http://www.informationweek.in/informationweek/news-analysis/297140/-driven-personalization

With the advent of web and social media the speed of the evolution of language has increased dramatically. There are many contributing factors to language that affect the changes. Big data takes linguistics to the next level and the technology like Hadoop helps in assisting interested parties in gaining deeper and clearer insights into linguistics. The reasons why Linguistics should be understand are that- Firstly, to benefit from the insights into linguistics provided by big data whether it may be vocabulary or grammar or something else. Secondly, today's technology continues to develop and improve, the use of voice commands for phones, TV's and game systems is going to increase and it's more important that developers understand the language people will be speaking to their devices in order to ensure the responsiveness. Big data will greatly enhance their ability to provide such speech oriented aspects. Thirdly, in case of learning a language and the way it is learned, understanding of linguistics matters a lot. Finally, to understand the past and looking to the future, it is again important to understand linguistics. With big data technology, the huge amount of data and information can be gathered and used to provide better insights into the past and future of language. Read more at:http://analytics.theiegroup.com/article/53bd6b6d3723a864d8000023/The-Impact-Of-Big-Data-On-Linguistics

Despite having the technological advancements which makes the process of job finding easier and user friendly, the whole thing is not so easy and in many cases it's more complicated. Here comes the role of Big Data which is now making its way into the field of recruitment and helps recruiters to find best people for the right positions. Some companies receive thousands of resumes for a single post and with such a huge number of resumes, companies are engaging in people analytics, applying big data analytics practices to a field of prospective job seekers. Many businesses build their own resumes of candidates by identifying details from people's social media profiles on Facebook, LinkedIn, Twitter, and other sites. From these profiles, companies use big data to identify patterns of behavior, interests, skills and attitudes that they are qualifying factors for current and future job openings. So, job seekers need to manage their profiles to get a job. But, as a negative impact, there are concerns over relying on it too much and as a matter of fact a heavy use of big data also takes factors like race, gender, and religion out of the equation. However, despite the drawbacks big data is of vital importance and job seekers should put themselves in a position to take advantage of big data and utilize it to get noticed.

Read more at:http://analytics.theiegroup.com/article/53b522e83723a80d7e000065/The-Modern-Job-Hunt-How-to-Beat-the-Big-Data-System

In today's world data is not only growing at a very fast rate but it is also being accessed and processed at unprecedented rate. So now, businesses have to focus on the velocity of Big Data, acting on it with precision for real-time results. This is where Fast Data comes in. Fast Data can provide real-time insights from events as and when they take place and help to make a decision at that place and point in time. Fast Data is complementary to Big Data for managing large quantities of real-time data. There are many examples of why Fast Data is becoming increasingly important. In a telecom industry, a Fast Data approach can help telecoms manage resources more effectively. In the financial services industry, Fast Data is using event correlation to contextualize available financial data. In retail industry, customer service centers are using Fast Data for click-stream analysis and customer experience management. Healthcare is another area where Fast Data holds huge potential. Read more at:

http://www.informationweek.in/informationweek/perspective/296992/speeding-business-transformation-fast