Big Data Analytics has started to make significant strides in less explored areas like improving manufacturing performance. No wonder the theme of ARC European Forum, 2015 was intended to help develop some clarity over emerging related concepts such as Industrie 4.0 and the Industrial Internet of Things (IIoT). Several use cases about how "applying these concepts can deliver tangible benefits in real-world industrial production across a broad cross-section of industrial sectors" were presented. Read More at: http://www.automationworld.com/industrial-internet-things/big-data-analytics-improve-manufacturing-performance

Inspite of the fact that Big Data analytics is found everywhere, the willingness of the firms to invest and to act on analytics insight is extremely slow. This is decision latency, where the companies have all the required data and knowledge but lacks the speed to make decisions on major issues. In today's world, data becomes less relevant with each passing minute. Traditional analytics tools face challenges in handling this data because they are designed to store and process the data but not to analyze this data from moment to moment. Three capabilities crucial for event processing systems to deliver ROI, are as follows :

1. High availability
2. User empowerment
3.  Empowerment of developers in order to built better distributed system with custom UIs (User Interface).

Read more at http://www.tibco.com/blog/2015/06/09/decision-latency-solving-the-big-data-analytics-oversight/

A firm needs to build a firm base that gradually can destroy others. The amount of information produced by social media platforms is an excellent way to measure a business’s both real and potential value. 56% of marketers named the ‘inability to tie social media to business outcomes’ as the central challenge to measuring ROI from social media. Gauging customer demand prior to launch using social media helps minimize risk, especially for entrants. Social media data can be correlated with an organization’s KPIs to know their impact upon one another indicating its usefulness. Allowing big data analytics capabilities to the social media platform helps firms to cross-reference social data to other data streams from their business. Read more about this article at: http://channels.theinnovationenterprise.com/articles/social-media-analytics

Micro lending is a way through which micro finance institutions (MFIs) provide micro credit to support entrepreneurship in rural areas. According to a Wall Street Journal report, experts have come up with ways that would make micro lending more effective. Instead of providing loans solely for investment purposes, MFIs could also lend for personal expenses if the borrower has the ability to pay back the loan with interest. Also, lenders should employ research to measure the success of the financial programs, making sure that the client not only returns the debt but does so while making a profit and not by selling his assets. Another way to make micro lending effective is to take up a holistic perspective. Quoting Iskenderian “Micro lending will be more effective if there are other safety-net and asset-building products in place—like insurance, savings and pensions—so that families can be secure and repay that loan.” Last but not the least is to make use technology for money transfer and big data analysis of mobile phone usage thereby easing out the whole process and saving time. Read more at: http://online.wsj.com/ad/article/mlf-5-ideas-to-make-microlending-more-effective

The global healthcare big data market is set to grow at 17 percent compounded annually according to the predictions of ResearchFox Consulting. Predictive and prescriptive analytics shall be the main area of focus in the United States. The Internet of Things (IoT) Industry is likely to get a big push from internet-enabled blood pressure monitors, mHealth apps, and wearable technologies. With the increasing need for interpolation of health data, improved healthcare coordination and robust big data analytics are becoming highly essential. Healthcare is in need of accurate data, real-time insights into patient care, and a better understanding of population health management, big data analytics is expected to gain importance. Read at: http://healthitanalytics.com/news/healthcare-big-data-analytics-driving-billions-in-market-growth

Big data analytics is the joining of two or more sources of information, so that it can be comprehended from the comparison of the new, expanded data set. Success with healthcare big data analytics relies on vendors, team of experts, and people who understands health management. Collecting and leveraging patient-generated health data from IoT devices will be the key in health care analytics. To know more how IoT helps in healthcare big data analytics, read this interesting article by Jennifer Bresnick (author) at: http://healthitanalytics.com/news/why-healthcare-big-data-analytics-needs-the-internet-of-things 

•  Big Data enables various capabilities like forensics and the analysis of long-term historical trends. By collecting data and analyzing historical trends, you would be able identify when an attack started, and what were the steps that the attacker took to get a hold of your systems. These techniques could play a key role to detect threats at an early stage. Big Data provides  opportunity to consolidate and analyze logs automatically from multiple sources rather than in isolation. This enhances intrusion detection systems (IDS) and intrusion prevention systems (IPS). Integrating information from physical security systems, such as building access controls and even CCTV, could also enhance IDS and IPS to a point where insider attacks and social engineering are factored in to the detection process. This presents the possibility of significantly more advanced detection of fraud and criminal activities. Big Data could result in far more practical and successful SIEM, IDS and IPS implementations. Read more at-         http://www.techrepublic.com/blog/big-data-analytics/how-big-data-is-changing-the-security-analytics-landscape/

Companies want to have an edge using analytics but struggle due to unavailable technologies, outdated software, cumbersome systems, complex integrations coupled with huge costs in infrastructure and personnel. The cloud has transformed the way organizations look at big data and analytics solutions. It has been predicted that investment in cloud over the next five years will grow threefold. • Open source platforms like Apache Spark provide simple and fast data processing capabilities. These though powerful, due to expensive hardware, long lead times are difficult to deploy. The cloud allows immediate usage of open source platforms without initial investments.
• Cloud -based software are user friendly, simple to grasp and sort in comparison to on premise counterparts and release cycles are shorter.
• Cloud-based analytics provide a platform where hard business problems can be effectively tackled.
• Processing and extracting data are easy from a synced centralized location.
• Better connectivity leads to better productivity, deployment of data pipeline is easy. Read more at:

http://insidebigdata.com/2015/05/08/5-reasons-data-analytics-in-the-cloud-will-take-center-stage-in-2015/

“Data is the new oil”

This comparison of big data with oil has always been there, ever since big data came into limelight. It is considered that like oil, the more you extract from big data, the more you benefit.

Now look at this new statement:

“Data is the new soil”

This statement reflects the growth in the field of big data. From being used only for extracting information, it is now being used to explore new avenues. Big Data is now being used as a raw material from which new ideas can be generated and further processed into new products and services. Many examples of this were given at Sapphire Now, SAP’s annual user conference, where innovators demonstrated various fields in which they have started using big data sets to create unique products. Some of them are:

• Handle the short and medium term challenges that climate change creates
• Help “local spaces” understand what mobile customers want
• Provide shoppers with a contextual in-store experience
• Help companies create solutions and discover things like energy and profit leaks, make predictable promotions based on clustered buyer preferences

Thus, big data is now providing a new range of solutions to make our lives easier as well as better. To know more, read the following article by Virginia Backaitis, Senior Partner at Brilliant Leap, at cmswire.com:

http://www.cmswire.com/cms/big-data/is-data-the-new-soil-sapphirenow-029124.php

The Global Food System comprises of a number of stakeholders as well as data - consumers, producers, economics, trade agreements, financial transactions, demand data, supply data, forecasting models, climatology, large and small-scale farms, politics, distribution systems etc. How do all of these correlate in a useful manner and show results? This is not possible with traditional scientific methodologies and technologies as there is a robust volume of complex data available. Rather, there’s a need for Big Data Analytics that will help in following areas:

• Measurement of poverty and hunger levels
• Improve aspects of how we feed and eat
• Food policy actions, etc.

Therefore, we need to invest in larger data warehouses which will provide the backbone for big data analysis of local, regional, national and ultimately, the global food system.

To know more, please read the following article by Hari Pulapaka, Executive Chef and Co-Owner, Cress Restaurant, at The Hufffington Post:

http://www.huffingtonpost.com/hari-pulapaka-phd-cec/big-data-analytics-the-gl_b_7216378.html?ir=India&adsSiteOverride=in

The hype around the word “big data” is ever increasing. It promises to bring a big revolution in marketing. But, in all this hype, myths also arise, which need to be cleared.

Joerg Niessing,INSEAD Affiliate Professor of Marketing, and James Walker, Partner Demand Analytics, Strategy&, in their article at knowledge.insead.edu, talk about eight commonly heard myths on big data. Some of them are:

• It’s big
• The more granular the data, the better
• Big Data is good data
• Big Data is a magic 8-ball

These myths need to be discarded before putting into use “the real Big Data”. To know more, please visit the following link:

http://knowledge.insead.edu/blog/insead-blog/the-eight-most-common-big-data-myths-3878

Big Data as a Service (BDaaS) means outsourcing various big data functions to the cloud, which includes supply of data, analytical tools to interrogate and analysis the data. Advantages of outsourcing your analytical activities are:

·         Organizations can save money spent on components and infrastructure and time.

·         Storing large quantity of information requires an ongoing investment of time and resources.  But by using BDaaS, organizations can concentrate on business only.

·         When data is stored on a BDaaS service provider server they are responsible for it.

·         Pay only for services you use on the basis of time used or the cost of compliance and data protection.
Read more at: http://www.forbes.com/sites/bernardmarr/2015/04/27/big-data-as-a-service-is-next-big-thing/

In today’s world, data is limitless. But, this Big Data, will help you achieve your targets, if we use it efficiently. Otherwise, you’ll be trapped in a web of data. For this, you need to do a gap analysis i.e. what data you have today and what data would you like to have.

To answer these questions, this article by Mary C. Long, Chief Ghost at Digital Media Ghost, suggests three tracks on which your business can move forward on:

1. Get a handle on your current data
2. Vet potential data sources and set a realistic budget
3. Add ONE new data source to your client insight capabilities

To know more, visit the following link on cmswire.com:

http://www.cmswire.com/cms/customer-experience/dont-let-big-data-keep-you-up-at-night-028895.php

Big data represents a major change in the way businesses and other organizations operate and will require a new mind-set and capabilities. Extracting business value from big data seems to be a complicated task. But, it can be easily accomplished, if done in a planned manner. Following article reports nine steps, given by HCL Technologies CEO, Anant Gupta, in the World Economic Forum’s Information Technology Report, to help organizations overcome the barriers in transition to Big Data and minimize the difficulties that may occur along the way:

http://www.information-age.com/it-management/strategy-and-innovation/123458030/9-steps-realising-benefits-big-datas-promise

Big Data Analytics is generally used for building models to periodically optimize processes i.e. After-it-Happens business. But this limits the use of Big Data as there is always a delay in the data-to-action cycle and also, the analytical capabilities are limited at the business’s disposal. A better application of big data analytics is using it for As-it-Happens business. It enables us to leverage the data and models moment by moment to make an impact on business operations in real time.

Steve Wooledge, Vice President of Product Marketing at MapR, gives examples of real life applications that leverage a big data environment that integrates OLTP and analytical databases in his following article:

http://www.forbes.com/sites/teradata/2015/04/09/creating-the-as-it-happens-business-analytics-drives-action/

According to Stefan Groschupf (CEO of Datameer), big data analytics can prevent healthcare industry from fraud as technology is providing powerful means to catch and prevent perpetrators.  Data-analytics will help in securing patient privacy and mitigating prescription fraud.  According to 2014 analysis of Standard & Poor's 500-stock index companies, it was found that healthcare and pharmaceutical companies have worse security performances. Big data analytics can be used to combine, integrate, and analyze data at once regardless of source, type, size, or format and identify   patterns needed to address fraud and compliance-related challenges. Big data can help to combine multiple data sources, analyze data and quickly deliver insights, pharmacies, doctor offices, and hospitals can track abnormal activity to mitigate prescription drug abuse. Read more at: http://venturebeat.com/2015/03/31/big-data-analytics-can-prevent-health-care-fraud-heres-how/

Many cricket teams are using Big Data Analytics to make important decisions about how to play and attack. There are sensors in the pitch and therefore we get loads of data per match which gives an opportunity to analyze this data with legacy data to make a very meaningful perspective. For example, we get data like- what % of balls by a bowler in a match are short pitch resulting in what % of total wickets or runs attributed to that type of balling in this match compared with past matches which makes the application of Big Data Analytics more meaningful. Read more at: http://tyronesystems.com/cwc/?p=1144

Big Data means different to different industry e.g. to computer manufacturers, big data analytics could mean demand for expensive servers and storage arrays; to the communications or cloud industry, the movement of data. But, for general people it means Big Data Analytics. The impact of change could be far-reaching and unpredictable. The budget spent on advertising via electronic, print and display media could costs double for data collection and analysis with impact which is immense. In the age of analytical marketing, we see firms collect more and more data in order to fine tune their analysis and increase competitive edge. To know more, follow Barry Schaeffer (principal consultant with Content Life Cycle Consulting)’s article link: http://www.cmswire.com/cms/big-data/look-before-you-leap-into-the-big-data-revolution-026873.php

vRad (Virtual Radiologic) released its latest Radiology Patient Care Indices, which will be available for free and unrestricted use.  It is the U.S.A.'s largest telemedicine company and radiology practice. It enables hospitals, health systems and radiology departments to use normalized data for comparing their own usage of CT imaging in the Emergency Department with similar organizations across the U.S. However, using analytics to improve measuring, benchmarking and proving overall healthcare value is not simple. One must know what to measure, how to measure it, and what benchmark goals to opt and a sound knowledge of radiology analytics. Read more at: http://www.vision-systems.com/marketwired/2014/10/14/vrad-continues-empowering-radiology-with-access-to-big-data-analytics-and-insights.html

According to Jason Bowden (a contributor to Business 2 Community), branding is a means by which a company is able to build their own identity and to communicate what their products and services are. In order to promote branding, brand managers always try to point out that their marketing campaign's focus is on consumers. These brand companies can learn more about their target customers with the help of big data analysis. The entry of data provides plentiful information that helps these companies in determining the various aspects that will yield better profit. Big data provide a window of opportunity for brand companies to know what products their target customers want. By instilling big data analytics, it is easier for marketers to know about their competitors and thus improve their digital marketing. There are other benefits in using big data. To know more about these benefits, follow: http://www.business2community.com/big-data/infusion-brand-marketing-big-data-analytics-0994537