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Showing posts with label Big Data. Show all posts
Showing posts with label Big Data. Show all posts

Thursday, October 18, 2012

Big Data To Drive $232 Billion In IT Spending Through 2016

Big data will drive $232 billion in spending through 2016. It will directly or indirectly drive $96 billion of worldwide IT spending in 2012, and is forecast to drive $120 billion of IT spending in 2013.
Gartner Research published the results today. They draw several conclusions from their research:
  • Big data is not a distinct market. More so, data is everywhere, impacting business in any imaginable way. Its influx will force a change in products, practices and solutions. The change is so rapid that companies may have to retire early existing solutions that are not up to par.
  • In 2012, “IT spending driven by big data functional demands will total $28 billion.”Most of that will go toward adapting existing solutions to new demands driven by machine data, social data and the unpredictable velocity that comes with it.
  • Making big data something that has a functional use will drive $4.3 billion in software sales in 2012. The balance will go toward IT services such as outside experts and internal staff.
  • New spending will go toward social media, social network analysis and content analytics with  up to 45% of new spending each year.
  • It will cost a significant amount in services to support big data efforts — as much as 20 times higher relative to software purchases. Peopel with the right skill sets are rare and in high demand.
That’s part of the story but the dynamics of memory, storage, and CPU capability provide context for what is happening in the market:
  • Memory doubled.
  • High speed and high-capacity networking technology pricing has decreased considerably.
  • Storage technology is moving from spinning disk to solid state disk and flash.
  • Enhanced CPU performance.
Storage management tops the list of sub-markets influenced by big data spending:
Big data technologies abound but customers need to consider how technologies will adapt over time. The Gartner report outlines how spending will initially grow due to the high need for services. People just don’t know how to get the value out of the data. Over time, the capabilities of the technology will decrease the need for services as practices standardize.
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Wednesday, October 17, 2012

'Serverless': A New Concept - Thanks to Cloud Computing




Cloud computing has simply removed a significant chunk of work around managing and provisioning services. The momentous rise of this technology has simply implied a shift in the future strategy of software and apps which are primarily occupied by servers.



The current scenario suggests that things are starting to change as more and more apps are moving into a serverless world.  This seismic shift definitely will bring large implications for the creation and distribution of software applications.  


The ‘Pre-Cloud’ Era:


Back then, developers where keen enough to think a lot about servers. They planned budgets, powered and housed them, and some even leased servers. Developers also had to consider cabling and cooling systems within their data centers.


But as years passed, things caught up into a drastic makeover. Developers finally realized the hardships in dealing and maintaining servers. As the allocation facilities began taking out many parts of the resources, detailed planning and preservation seemed pretty waste.


Enter the cloud:


In the last two years, the tech world has subjected to a huge shift in terms of computing. Trends like cloud and BYOD have taken their own stand. Questions such as "Why cloud?" or even "How cloud?" are no longer to be heard. Infrastructure-as-a-Service (IaaS) has delivered dramatic improvement on cost, agility, scalability and reliability.


With almost limitless amount of virtual machines available, developers are so pumped up that they can chose  any operating system they wish to, load in their applications and even start profiting from them. Even launching hundreds of servers and coordinating is still far better when compared to what it was just six years ago.

Application in the “Cloud”:


The standalone applications built on Ruby, Rails, Python or any other Web app frameworks are giving way to a distributed system spread across a number of applications, processes and data stores. The concept on building a web app has changed. At present, it’s all about building apps that consist of loosely coupled components scattered across the cloud.


This trend has clearly outlined the fact that applications aren’t anymore server-based. At present, processing is increasingly taking place outside of an app framework. Assisting these processes are client apps and back-end data storages. In short, developers are on the verge of becoming serverless.


Thinking Serverless:


“Serverless” doesn’t mean servers are no longer involved. It means that developers no longer have to think much about them. A change in strategy is what we see, as service providers are increasingly taking the responsibility of managing servers, data stores and other infrastructural resources. This gives an increased advantage for developers as they no longer have to deal with additional physical commodities or limits.


Related articles
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Tuesday, October 16, 2012

Soon You'll be able to store 10 TB of data on Finger-Nail sized Device


10 Terabytes


A new discovery may open the way for the development of next generation data storage devices with capacities of up to 10 terabits (10 trillion bits) per square inch - vastly enhancing storage on much smaller data devices.


Imagine storing thousands of songs and high-resolution images on data devices no bigger than a fingernail.


An ultra-smooth surface may be the answer, according to a discovery by the researchers from Agency for Science, Technology and Research's (ASTAR) Institute of Materials Research and Engineering (IMRE) and the National University of Singapore (NUS), reports the journal Nature reports.


The self-assembly technique is one of the simplest and cheapest high-volume methods for creating uniform, densely-packed nanostructures that could potentially help store data, according to an ASTAR statement.


However, attempts to employ self-assembly on different surface types, such as magnetic media used for data storage, have shown varying and erratic results to date. This phenomenon has continued to puzzle industry researchers and scientists globally.


Researchers from ASTAR have now solved this mystery and identified that the smoother the surface, the more efficient the self-assembly of nanostructures will be.


This breakthrough allows the method to be used on more surfaces and reduces the number of defects in an industrial setting. The more densely packed the structures are in a given area, the higher the amount of data that can be stored.


"A height close to 10 atoms, or 10 angstroms in technical terms, is all it takes to make or break self-assembly," said MSM Saifullah, one of the key researchers from ASTAR's IMRE who made the discovery. This is based on a root mean squared surface roughness of five angstrom.


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Wednesday, October 10, 2012

Why Big Data Analytics Really Matters to Marketers

You’ve spent countless hours and probably a lot of dollars (social media marketing is expected to hit $3.1B by 2014) building meaningful social media marketing programs. If implemented properly, they have helped increase conversations happening about your brand. But now what? How do you measure the business impact of your ongoing social media engagement to justify the marketing spend? The old adage in marketing is very true in social media, you waste 50% of all of your marketing spend; the challenge is finding the effective 50%.

Sure, you can measure the stuff that fits into a spreadsheet like number of new followers, re-tweets, link click-through, Klout scores, or any other number of web click things. For networks like Twitter, you can diagram the network, identify reputation, prestige and reach, and look at path lengths between nodes in the network.  A lot of folks already do that.

But rather than just social network stats and graphs, what you really want to know is how social media is addressing your business problems. Is it driving more revenue, reducing customer churn, turning more visitors into customers or increasing customer satisfaction?

The truth is that, historically, there’s been no easy way to tell how your social media programs are really affecting the bottom line. In order to understand the actual impact of social media, you need to be able to look at your social media results in conjunction with other data sources. And the only way to do that is by using Big Data analytics.

Big Data What?

To fully understand why you should care about Big Data analytics, first you need to understand what Big Data is. It’s exactly the problem you’re facing right now – it’s lots of data from a lot of different sources, it’s coming in faster than ever and it’s not the sort of data that fits into Excel. A lot of this is what as known as “semi-structured” or “unstructured data”. Its your social media feeds, its your call center records, its any and every type of data that you might want to harness and make sense of to help make fact-based business decisions.

So what can you do with it?

Quite simply, big data analytics makes it possible for your company to integrate, analyze and visualize all of this data. You can use it to understand customer sentiment from social media programs, and get a more complete view of what your customers are actually doing in response to social media. You can identify the best influencer hubs based on quantified results rather than best guess. You can identify missed revenue opportunities and better target advertising.  All made possible because you were able to see a complete view of prospects and customer across social media and other customer touch points like call centers and website interactions together with in-store or web store transactions. It actually allows you to better understand the “results” from all of this social media attention. Because you can correlate disparate data sets, you can actually ask your data if and how positive customer sentiment drives revenue, and who are the best influencers, not simply the most prolific.

Great, but how?

In addition to all of your social media data, you have lots of different data sources in your business that contains customer and/or prospect interaction or transaction data.  Customer/prospect information from salesforce.com and marketing campaign data from Marketo. Clickstream data from Omniture. Transaction system records. Call center logs. Product catalog data. The list is endless. Individually each of those data sources provide a finite amount of insight and are typically analyzed alone and can only provide visibility on that single data source. Correlating these datasets is the key to proving the worth of your social media programs.

The magic happens when you combine these datasets with each other to ask the sorts of questions you’ve always wondered. “When X retweets me, is there a spike in my sales?” “When Y posts on my timeline, is there an increase at my call center?” “Does my advertising campaign help drive people to our Facebook page?” The resulting metrics allow you to tweak various social media, traditional marketing, or advertising campaigns so that your social media “score” goes up. This is what we call having a 360-degree view of your business (see diagram below), and it’s only possible with big data analytics.

The entire process boils down to three steps:

1.    Data integration – getting all the data in one place for ease of analysis

2.    Analytics – actually transforming and analyzing the data so that you can correlate between social interaction and resulting transactions

3.    Visualization – visual representations of your analysis to easily see important correlations and actual results

Now that you know there is a way to get from social media metrics to meaningful business decisions, it’s time to make the case once and for all that social media programs are an integral part of the marketing mix, and ultimately, business strategy. To do that, you must capture, correlate, analyze, and visualize all of your relevant data sets.  Otherwise, you’re simply looking at your business through a soda straw with little understanding of what really affects your bottom line and why. And you won’t see the competition coming until they hit you.

Monday, October 8, 2012

Big data: Latest trend after cloud computing

With the management of new types of data rising in priority, Indian organizations are increasingly seeing the opportunity in big data, the latest trend after cloud computing and virtualization to create a buzz in India.


A new survey by Informatica Corporation revealed that 72 per cent of Indian organizations are now considering, planning or running 'Big Data' projects, with organizations viewing the trend as an opportunity rather than an IT challenge by a greater than two-to-one margin in India.

Meanwhile, the management of big interaction data - including social media data (26 per cent), mobile device data (21 per cent) and machine-generated data (16 per cent) - is very much rising in relevance due to the insights, efficiencies and customer engagement these new data types can help drive.

Organizations intend to get a wide variety of benefits from their big data efforts, according to survey respondents. Improving efficiency in business operations by doing more things with more data is the number one business driver (55 per cent). This is followed by attracting and retaining customers (38 per cent).

However, lack of maturity in big data tools is the top challenge (42 per cent) that respondents face in big data projects. Lack of support for real-time streaming data is another key challenge (32 per cent), followed by concerns around data security and privacy (30 per cent).

In addition, respondents cited the difficulty and time involved in developing in emerging technologies (27 per cent), challenges faced due to poor data quality (21 per cent), and the limited availability of skilled developers to manage big data (23 per cent).

Sunday, October 7, 2012

Alteryx Opens Big Data-Analytics Apps Studio For The Rest Of Us

alteryxlogo

Alteryx has opened a big data-analytics apps studio for people who do not necessarily have a deep knowledge of data science. The service is available as part of Alteryx 8.0, the analytics provider’s latest release. The intent is to make data analytics as accessible as a consumer application makes its service.

I tried playing with the apps. I used a Twitter tool to track tweets about Oracle. The results were relatively decent. A number of the apps in the studio are for the retail market, but there are also those that can be used for any business. For instance, there is a U.S. Census app for conducting demographic analysis.

Here’s an example of a retail app:

People may use the apps, collect and share data with colleagues — similar to the experience in a consumer app store. It also includes a desktop app builder.

George Mathew, president and chief operating officer of Alteryx, said the intent is to create a service that is not just the domain of a small community of data scientists. More so, it’s for the 2.5 million data analysts in the market who can use the tools to drive big data analytics into any kind of an organization.

Alteryx represents a trend with big data-service providers to take the information and expertise of data geeks and make it accessible through an app. For instance, Prior Knowledge, a TechCrunch Disrupt finalist, has developed a way for app developers to add a level of predictive analytics without the need to have deep knowledge of statistical analysis. The expertise is built into the Prior Knowledge technology. And on Friday, I featured Lytics, a service that tackles the problem that comes with getting value out of data from multiple sources such as mobile environments, the web, email, social, third-party APIs and commerce environments. Lytics customers use it to optimize pricing and inventory and multiple other aspects of the business that can draw from data to improve the queries and results.

Saturday, October 6, 2012

Big data: Latest trend after cloud computing

Big Data

With the management of new types of data rising in priority, Indian organizations are increasingly seeing the opportunity in big data, the latest trend after cloud computing and virtualization to create a buzz in India.

A new survey by Informatica Corporation revealed that 72 per cent of Indian organizations are now considering, planning or running 'Big Data' projects, with organizations viewing the trend as an opportunity rather than an IT challenge by a greater than two-to-one margin in India.

Meanwhile, the management of big interaction data - including social media data (26 per cent), mobile device data (21 per cent) and machine-generated data (16 per cent) - is very much rising in relevance due to the insights, efficiencies and customer engagement these new data types can help drive.

Organizations intend to get a wide variety of benefits from their big data efforts, according to survey respondents. Improving efficiency in business operations by doing more things with more data is the number one business driver (55 per cent). This is followed by attracting and retaining customers (38 per cent).

However, lack of maturity in big data tools is the top challenge (42 per cent) that respondents face in big data projects. Lack of support for real-time streaming data is another key challenge (32 per cent), followed by concerns around data security and privacy (30 per cent).

In addition, respondents cited the difficulty and time involved in developing in emerging technologies (27 per cent), challenges faced due to poor data quality (21 per cent), and the limited availability of skilled developers to manage big data (23 per cent).


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