Friday, 17 July 2015

6 Predictions For The $125 Billion Big Data Analytics Market in 2015: Big Data Analytics ; Data Mining Science Training @ Epoch Research Institute India Largest SAS Training


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Source: Gil Press, Contributor


The big data and analytics market will reach $125 billion worldwide in 2015, according to IDC. Both IDC and The International Institute of Analytics (IIA) discussed their big data and analytics predictions for 2015 in separate webcasts yesterday. Here are the highlights:
Security will become the killer app for big data analytics

Big data analytics tools will be the first line of defense, combining machine learning, text mining and ontology modeling to provide holistic and integrated security threat prediction, detection, and deterrence and prevention programs. (IIA)
IoT analytics will be hot, with a five-year CAGR of 30%

The Internet of Things (IoT) will be the next critical focus for data/analytics services. (IDC) While the IoT trend has focused on the data generation and production (sensors) side of the equation, the “Analytics” of Things is a particular form of big data analytics that often involves anomaly detection and “bringing the data to the analytics.” (IIA)
Adoption of technology to continuously analyze streams of events will accelerate in 2015—it’s all about speed and small units of data. IoT back end as a service (BaaS) will emerge, as players—including Amazon, IBM IBM -1.2%, andMicrosoft MSFT -1.2%—continue to stitch together a wider variety of platform as a service (PaaS) services, including stream processing, data triggers, indexing and synchronization, and notifications, into more tightly integrated offerings directly marketed to the growing community of IoT developers. (IDC)

Buying and selling data will become the new business bread and butter 70% of large organizations already purchase external data and 100% will do so by 2019. In parallel, more organizations will begin to monetize their data by selling them or providing value added content. (IDC) Companies will double their investment in generating new and unique data. “You can’t go into a data-based business without some unique data that gives you competitive differentiation.” 2015 will mark an inflection point of intentional investment by mainstream firms in generating and monetizing new and unique data sources. (IIA)
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I am Chetan from Maharashtra and i am really glad to join ETCS as SAS Consultant. After i completed my graduation in BCA, i was struggling to find a correct path for my career. at that time i came to know about SAS. After taking some time to decide which institute i should go for, i  realized  that Epoch is the only accredited Training  institute for SAS in India. I attended the counselling session  which gave me all the information i needed to know about my future career ambitions. I joined the course and my training 
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Why is big data analytics important?: SAS Training on Big Data Analytics @ : Epoch Research Institute India Pvt. Ltd. (www.epoch.co.in)


SAS Training On Visual Analytics. Epoch Research


For years SAS customers have evolved their analytics methods from a reactive view into a proactive approach using predictive and prescriptive analytics. Both reactive and proactive approaches are used by organizations, but let's look closely at what is best for your organization and task at hand.




Reactive vs. proactive approaches

There are four approaches to analytics, and each falls within the reactive or proactive category:
  • Reactive – business intelligence. In the reactive category, business intelligence (BI) provides standard business reports, ad hoc reports, OLAP and even alerts and notifications based on analytics. This ad hoc analysis looks at the static past, which has its purpose in a limited number of situations.
  • Reactive – big data BI. When reporting pulls from huge data sets, we can say this is performing big data BI. But decisions based on these two methods are still reactionary.
  • Proactive – big analytics. Making forward-looking, proactive decisions requires proactive big analytics like optimization, predictive modeling, text mining, forecasting and statistical analysis. They allow you to identify trends, spot weaknesses or determine conditions for making decisions about the future. But although it's proactive, big analytics cannot be performed on big data because traditional storage environments and processing times cannot keep up.
  • Proactive – big data analytics. By using big data analytics you can extract only the relevant information from terabytes, petabytes and exabytes, and analyze it to transform your business decisions for the future. Becoming proactive with big data analytics isn't a one-time endeavor; it is more of a culture change – a new way of gaining ground by freeing your analysts and decision makers to meet the future with sound knowledge and insight.
With SAS, you can truly change operations, prevent fraud, gain competitive edge, retain more customers, anticipate disease outbreaks or run unlimited budget simulations – the possibilities are endless.

Source :  http://blogs.sas.com/content/sastraining



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