Top 10 Big Data Articles You Must Read Today

1. Big Data: Now A Top Management Issue For 2016

A new study by the Economist Intelligence Unit shows how big data is moving from its infancy to a “data adolescence,” in which companies are increasingly meeting the challenges of a data-driven world.

The report, called “Big Data Evolution,” details the ways in which companies’ attitudes and activities have changed over the past four years with regards to big data — collecting it, storing it, analyzing it, and using it to make business decisions about strategy. Continue reading…

2. 6 Predictions For Big Data Analytics And Cognitive Computing In 2016

Big data analytics is the next trillion-dollar market, says Michael Dell. IDC has a more modest and specific prediction, forecasting the market for big data technology and services to grow at a 23.1% compound annual growth rate, reaching $48.6 billion in 2019. Continue reading…

3. 7 Important Big Data Trends for 2016

It is the end of the year again and that means it is time for the Big Data trends for next year. I did that for 2014, I did it for 2015 and now it is time for 2016. What is awaiting us in 2016? Which Big Data trends will have an impact on the global Big Data domain? How will Big Data affect organizations in 2016? Let’s have a look at seven of the most important Big Data trends for the year 2016. Continue reading…

4. Lack of Big Data Talent Hampers Corporate Analytics

A shallow talent pool of skilled workers to analyze big data, combined with the challenge of weeding out bad information, continues to cause nightmares for CIOs.

kalid khan at kearney Khalid Khan, partner at A.T. Kearney.
Two-thirds of companies that possess even the most advanced analytics capabilities cannot hire enough people who can generate insights from corporate data, according to new research from A.T. Kearney, which surveyed 430 senior executives. Moreover, companies will need 33 percent more big data talent over the next five years, says Khalid Khan, A.T. Kearney partner and co-author of the research. Continue reading…

5. Big Data Still Requires Humans To Make Meaningful Connections

Big data is a big deal, make no mistake about it, but it’s probably not as big a deal as it’s going to be eventually when we really figure out how to make good use of it. For now, we have this muddled middle where we understand the value of the data, but most organizations and governments don’t know how to use that data to its full potential. Continue reading…

6. The 10 Coolest Big Data Products Of 2015

The big data technology market remains one of the fastest growing segments of the IT industry. In November, market research firm IDC said the market for big data-related infrastructure, software and services will grow at a compound annual growth rate of 23.1 percent through 2019, with spending reaching $48.6 billion in 2019. Specifically, sales of big data software are expected to grow at a CAGR of 26.2 percent during that span. Continue reading…

7. Where Does Big Data Fit Into Marketing?

Where does your big data fit in to your marketing? This is a very tricky question. Of course you want to capture customer information as much as possible so that your marketing team can be much smarter about the method they use to communicate to prospects and existing customers. BUT, marketers first need to decide if the brand wants them to create a sales promotional strategy or a brand building strategy. Continue reading…

8. Misconceptions Regarding Big Data And Why It’s Important To Clarify Those?

There is a lot of hype around big data, and this, to a certain extent is harmful for businesses. Sounds shocking? Well, since there are so many articles, research reports and studies about big data, people are provided with more than enough information, and this, somewhere down the line, makes big data look too easy to understand. This is where all the problems begin since even before knowing the original features and characteristics of this new phenomenon, people start assuming a lot. As a result, a lot of misconceptions get generated. Continue reading…

9. Big Buzz About Big Data: 5 Ways Big Data Is Changing Finance

Big Data is a big deal… particularly for financial markets. As the CEO of a Big Data company, I’d like to share with you some insights into this shift, which is spurring transparency, capital availability and better risk awareness. Add in the coolness and creativity factors – more Sand Hill Road, less Wall Street – and it’s clear that Big Data is already having big impacts on always-changing financial markets. And this is change that you, not just your IT professionals, should believe in. Continue reading…

10. Where Mobile is Failing: Big Data

Big data has been a big buzzword in advertising for several years now. Alas, for many mobile advertisers, it remains just that: A buzzword and not something they’re actually using to better target their ads or focus their media plans. That’s according to a new study conducted by Forrester Research and real time ad bidding platform AdTheorent. Continue reading…

Data analytics isn’t about Insights. Idexcel Big Data Roundup

1. How To Use Data To Outsmart Your Competitors

The pressure’s on to use data to outsmart your competitors. Here are six ways companies can use data to imagine and even re-imagine what’s possible.

“Business as usual” can be a risky business practice, especially when there’s cultural resistance to change. While some companies are embracing agile practices, there are a number of data-related barriers that keep companies from reaching their potential, most of which have to do with people, processes, and technology. Read more…

2. Ten Ways Big Data Is Revolutionizing Supply Chain Management

Bottom line: Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.

Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems. For manufacturers whose business models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck. Designed for delivering order, shipment and transactional data, these systems aren’t capable of scaling to meet the challenges supply chains face today. Read more…

3. How Data Projects Drive Revenue Goals

The vast majority of organizations have either already implemented a big data project or plan to do so, according to a recent survey from CA Technologies. The report, titled “The State of Big Data Infrastructure: Benchmarking Global Big Data Users to Drive Future Performance,” indicates that a great deal of these projects are integrated throughout the entire organization. Companies are pursuing big data and analytics primarily to improve the consumer experience while adding to their customer base. However, there are formidable challenges, including a lack of trained staffing to make data projects succeed, as well as the inherent complications of such implementations. Read more…

4. Importance of Big Data Analytics for Business Growth

Until recent years companies have always evaded the question of using data analytics for business execution, leave alone big data. Most of the time it was due to cost of analysis that the organisations kept in mind while keeping away from data analytics. With everything going digital, data is pouring in from all kinds of sources imaginable. Organisations are getting inundated with terabytes and petabytes of data in different formats from sources like operational and transactional systems, customer service points, and mobile and web media. The problem of such huge data is storage and with no proper utilisation of the data, collecting and storing is a waste of resource. Earlier it had been difficult to process such data without relevant technology. Read more…

Big Data: The Engine Driving the Next Era of Computing

You are at a conference. Top business honchos are huddled together with their Excel sheets and paraphernalia. The speaker whips out his palmtop and mutters ‘big data’. There follows an impressive hush. Everyone plays along. You feel emboldened to ask, “Can you define it?” Another hush follows. The big daddys of business are momentarily at a loss. Perhaps they can only Google. You get it? Everyone knows, everyone accepts, big data is big, but no one really knows how, or why. At any rate, no one knows enough straight off the bat.

In the Beginning was Data. Then data defined the world. Now big data is now refining the data-driven world. God is in the last-mile detail. Example: In the number-crunching world of accountancy, intangibles are invading the balance sheet values. “Goodwill” is treated as an expense. It morphs into an asset only when it is acquired externally like say, through a market transaction. Data scientists now ask why can’t we classify Amazon’s vast data pool of its customers as an “asset”? Think of it as the latest straw in the wind of how big data is getting bigger.

Big data is getting bigger and bigger because data today is valued as an economic input as well as an output. The time for austerity is past. Now is the time for audacity. Ask how. Answer: Try crowd sourcing your data defining skills.

When you were not watching, big data was changing the way the technology enablers play the game in the next era of computing. Applications are doing a lot more for a lot less.

Big data isn’t about bits or even gigabytes. It’s about talent. Used wisely, it helps you to take decisions you trust. Naysayers of course see the half-full glass as if it is under threat of an overspill. They insinuate that big data leads to relationships that are unreal. But the reality we don’t know is what is behind all that big data. It is after all, a massy and classy potpourri: part math, part data, with some intuition thrown in. It’s ok if you can’t figure out the math in the big data, because it is all wired in the brain, and certainly not fiction or a fictitious figment of imagination.
When you were not watching, big data was changing the way the technology enablers play the game in the next era of computing. Applications are doing a lot more for a lot less. Just to F5 (we mean refresh…):
You and me can flaunt a dirt cheap $50 computer the size of your palm AND use the same search analysis software that is run by obscenely wealthy Google.

Every physical thing is getting connected, somewhere, at some time or the other, in some or the other ways. AT&T claims a staggering 20,000% growth on wireless traffic over the past 5 years. Cisco expects IP traffic to leap frog ahead and grow four-fold by 2016. And Morgan Stanley breezes through an entire gamut of portfolio analysis, sentiment analysis, predictive analysis, et al for all its large scale investments with the help of Hadoop, the top dog for analyzing complex data. Retail giant Amazon uses one million Hadoop clusters to support their affiliate network, risk management, machine learning, website updates and lots more stuff that works for us.

Data critics though are valiantly trying to hoist big data on its own petard by demanding proof of its efficacy. Proof? Why? Do we really need to prove that we have never ever had a greater, better analyzed, more pervasive, or expansively connected computing power and information at a cheaper price in the history of the world? Give the lovable data devil its due!