Big data analytics finds immense application across the entire business. One area which can have direct, measurable and visible impact is the area of customer service. Data has been used since time immemorial to improve customer service, but it is only recently that the full power of predictive analytics is being applied in this function. Organizations, both large and small, are using big data…Continue
Added by Aureus Analyitcs on November 24, 2015 at 1:00am — No Comments
“Predictive analytics” is a commonly used term today. Wikipedia describes it as ‘encompassing a variety of statistical techniques from modeling, machine learning, and data mining that analyze current and historical…Continue
Added by Aureus Analyitcs on November 21, 2015 at 12:30am — No Comments
Consistency is critical to business since it ensures results that can be tangibly seen. In insurance industry, the policy is profitable for the insurer only when the policy persists within the insurers’ portfolio for a certain period of time. Typically Life insurance has a longer persistency period to recover the costs and become profitable compared to a general insurance portfolio.…Continue
Added by Aureus Analyitcs on November 19, 2015 at 10:00pm — No Comments
The global big data market is likely to grow from US$6.3 billion in 2012 to US$48.3 billion in 2018.The research report states that registering a remarkable CAGR of 40.5% from 2012 to 2018, The report studies the global big data market by segmenting it on the basis of four criteria: product requirement, component, application, and geography. By component, the big data market is categorized into hardware, software and services, and…Continue
Added by sagar Gavhane on November 19, 2015 at 9:27pm — No Comments
Everyone has been talking about how social data can help them retain customers and improve revenues and increase profit and get more customer and get more revenue and … you get the point.…Continue
Added by Aureus Analyitcs on November 17, 2015 at 10:44pm — No Comments
At breakfast last week, my wife and I noticed water dripping out from under our coffee maker.
Saeco Barista, circa 2004 source:…Continue
Added by Cameron Turner on November 13, 2015 at 8:31am — No Comments
From the consummate safety of his bunker, Posh Dave surveyed the magnificently pastoral pastel shades painted by God herself on the canvas that is the Pacific Ocean. "How on earth" he thought, "can people die of thirst and polluted water, when we have so much fresh, clean and pristine water on this goddam planet?"
The Data Leviathan, Martyn Jones
This may come as a surprise to some people who know my opinions on the subjects of data in…Continue
There is no doubt that when an enterprise’s customer base and product portfolio grows, it becomes even more complicated to manage multiple relationships with the customer across products, channels and geographies. Most organizations have a simplistic approach to manage this challenge: Customer Single View.…Continue
Added by Aureus Analyitcs on November 8, 2015 at 10:30pm — No Comments
The dictionary meaning of ANALYTICS - Picking up the most important one from many. That's it nothing else. Call it Web Analytics/Bigdata Analytics/Predictive Analytics/Business Analytics... The target of any form of analytics is just to pick the most…
Variety, Velocity, Volume and Veracity are the four Vs for Big Data. Most of the technologies available have shown how to treat the Volume. However, due to the increasing number of streaming data sources, the Velocity problem is as relevant as never before. Moreover, Veracity and especially Variety problems have increased the difficulty of the challenge.…Continue
Added by Amit Sheth on November 5, 2015 at 8:30am — No Comments
Picking up from where we left off in the last part, here is a list of some more of the big data terminologies simplified…Continue
Added by Aureus Analyitcs on October 30, 2015 at 9:00pm — No Comments
Hadoop, named after a toy elephant that belonged to the child of one its inventors, is an open-source software framework. It is capable of storing colossal amounts of data and handling massive applications and jobs endlessly. Hadoop’s capabilities make it one of the most sought after data platforms for successful businesses all over the world.
Because it can store and quickly process any type of data, Hadoop is lightyears ahead of the game in the…Continue
Last year, “Big Data” was THE buzz word. And while Big Data is still buzzing about, marketers today are using the term more frequently as part of their everyday conversations, at least to some extent. It is clear that “Big Data” is no longer just a snazzy new word to use when marketers talk “shop,” but rather a concept that has proven its worth.
However, before running head-first into the…Continue
Added by Larisa Bedgood on October 28, 2015 at 11:01am — No Comments
Added by Damian Mingle on October 28, 2015 at 7:01am — No Comments
The big data analytics space is evolving at a tremendous speed, so is the terminology used in the space. This terminology is sometimes really hard to understand. Here is a list of some of the big data terminologies simplified.…Continue
Added by Aureus Analyitcs on October 19, 2015 at 10:00pm — No Comments
A few months ago, we posted this…
Added by Larisa Bedgood on October 19, 2015 at 9:22am — No Comments
Each organizations these days is after collecting data about its customers. But very few use this data to optimum use.
Most of the organizations are clueless about the huge chunk of data that is available with them. Many companies expect the data to answer their questions. But they forget that data doesn't answer on its own. It is the analytics which help the companies give meaning to the data and provide solutions to the queries. So it is important to know the questions one has to…Continue
Added by Aureus Analyitcs on October 16, 2015 at 10:30pm — No Comments
The song will never work. It’s too long, too complex,
too confusing and doesn’t fit into any musical genre.
– Radio stations’ feedback to Queen aboutBohemian Rhapsody
Search of greater return on Big Data investment or generating alternative revenue stream for your organization.No matter the situation, let’s go through some of the most common myths of data monetization.
- Not Every Bit…Continue
Added by vivek upadhyay on October 13, 2015 at 10:57pm — No Comments
Business goals are no doubt important, but…Continue
Added by Damian Mingle on October 13, 2015 at 5:59pm — No Comments
When I try to explain Data Science and Analytics to business people or those interested in these fields, I use the following example to describe the four pillars of: Data, Platform/Tools, Algorithms, and know-how.
To me, "data" is like a collection of bones (say of an animal) scattered around, some clean and some hidden in dirt. If these pieces are collected and put together correctly, it will mimic or resemble the real skeleton of that animal. Some of the bone pieces are…Continue
Added by Khosrow Hassibi on October 13, 2015 at 7:39am — No Comments