Age of Big Data– Mining for Value to Fuel Growth: Understand-Extract Real Business Value– Key Competitive Differentiator…

Big Data: Every day, we create 2.5 quintillion bytes of data (i.e., 2.5 followed by 18 zeros)— so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few…

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Big Data: We swim in a sea of data… and the sea level is rising rapidly. Tens of millions of connected people, billions of sensors, trillions of transactions work to create unimaginable amounts of information… According to Janna Anderson and Lee Rainie; an equivalent amount of data is generated by people simply going about their lives, creating what the ‘McKinsey Global Institute’ calls ‘digital exhaust’– data given off as byproduct of other activities such as; Internet browsing-searching, smartphone usage…

Human-created information is only part of the story, and a relatively shrinking part, for example; there are machines and implanted sensors in oceans, in the soil, in pallets of products, in gambling casino chips, in pet collars, and countless other places are generating data and sharing it directly with data ‘readers’ and other machines that do not involve human intervention. The projected growth of data from all kinds of sources is staggering– to the point where some worry that in foreseeable future the digital systems of storage and dissemination will not be able to keep-up with the simple act of finding places to keep the data…

According to McKinsey; research finds that data can create significant value for world economy, enhancing productivity and competitiveness of companies and the public sector and creating substantial economic surplus for consumers… However, while enthusiasts see great potential for using Big Data, privacy advocates are worried as more and more data is collected about people– both as they knowingly disclose things in such things as their postings through social media and as they unknowingly share digital details about themselves as they march through life.

Not only do the advocates worry about profiling, they also worry that those who crunch Big Data with algorithms might draw the wrong conclusions; e.g., about who someone is, how one might behave in the future, and how to apply the correlations that emerge in the data analysis… There are also plenty of technical problems. Much of the data being generated now is ‘unstructured’ and sloppily organized. Getting it into shape for analysis is no tiny task….

The Biggest Trends in Business–The Rise of Big Data: Big Data is the vast (and ever-growing) stockpile of information too large for companies to store in-house–let alone analyze. All that data offers potential opportunities for cutting-edge businesses willing to step-up and do the data crunching.

According to IBM; 2.5 quintillion bytes of data are born every day (i.e., enough to fill more than 531 million DVDs), and 90% of the world’s digital information was produced over the last two years. For so long, we’ve focused on human-powered businesses, and now we’re transforming into data-driven organizations that are bringing a level of customer centricity that we’ve never seen before. And, this is just early stage of the info boom.

According to Computer Sciences Corporation; by 2020, the annual data-generation rate will balloon 4,300% to 35 zettabytes of data (i.e., 7.35 trillion DVDs). According to Reuters; venture capital firms invested $2.47 billion in fields around Big Data in 2011, nearly 10% of all money distributed. That’s up from $1.53 billion in 2010 and $1.1 billion in 2009

According to Matt Ocko; Big Data represents a transformation of the entire IT industry, and $300 billion to $500 billion of wealth-creation opportunity for business. 

According to McKinsey Global Institute; the potential value of Big Data, when used creatively and effectively by the U.S. healthcare industry, would be worth more than $300 billion, in that sector alone each year. Currently, healthcare providers throw 90% of that information away… And that’s just one of many market segments that Big Data will revolutionize…

No matter how you look at it– as a consumer, marketer, investor, administrator or inventor– numbers don’t lie. Big Data isn’t just changing business; it’s changing everything…

In the article What Is Big Data and Why Does It Matter? by Margaret Dawson writes: Big Data doesn’t necessarily have to involve huge amounts of data, since it’s more about the quality of information you need to garner from the data and how difficult it’s to process and gain intelligence from it, rather than the pure size. While ‘data mining’ and ‘business intelligence’ are not new, Big Data takes these fields to a new level– dealing with data, ‘structured’ and ‘unstructured’, across multiple sources and applications in a dynamic, and near real-time fashion…

According to Sanjay Sarathy, perhaps most importantly; Big Data uses data as a new source of competitive opportunity and success. While most companies discuss and define Big Data in the context of the 3-V’s (i.e., volume, velocity and variety), another way to think about Big Data is the fact that most of it is; a) unknown, and b) unmanageable to IT organizations.

The relevance of Big Data is significant because– hidden among the daily terabytes (i.e., one trillion bytes) that a single organization can generate are insights that lead to better customer service, improve revenues, and deeper market understanding…

According to David Jonker; first and foremost Big Data is an emerging trend where companies are harnessing their data in order to drive business value. So Big Data is an opportunity; companies are seeing the value in tracking new business indicators that were not possible before. To truly harness Big Data opportunities, enterprises need to rethink how they manage data…

In the article Rise Of Machines–Why Big Data Is Getting Bigger by James Murray writes: Machine data is now the fastest growing element of Big Data and is set to represent 90% of all data. The ability to analyze-derive insight from all this machine data is where the big prize, but up until now its value has been largely ignored by business. This is a major oversight, as the information generated by machines can paint a richer and far more detailed picture of the operational health of an organization than any other measure.

But machine data doesn’t just apply to large IT systems– anytime someone switches on a phone, turns on a laptop, moves a mouse… machine data is generated. Some business are waking up to the value of machine data; integrating it into the Big Data mix to get a fuller, more holistic overview of how their company works. And this goes way beyond traditional notions of ‘business intelligence’, looking in the rear-view mirror of historical data to try to understand what you should do next: This is about ‘operational intelligence’, making decisions based on a constantly updated real-time snapshot of the business.

Machine data is changing the business landscape irrevocably; as Big Data is becoming increasingly pervasive and as technology underpins everything we do. For business worldwide, it opens up the potential to genuinely revolutionize the way they work– the challenge now is to manage and control machine data without becoming overwhelmed by it…

In the article Big Data And How Social Media Uses It by Social Media writes: While social media sites are pretty specific in the data they receive, some sites receive so much data; it takes far more than simple analytical tools to make sense of it all; every mouse click, post, tweet, invoice, and settlement for companies is being recorded

This could include; e-commerce, scientific experiments, environmental research, social data (taking in more than one site), and web activity to name just a few. In addition, these sectors require numerous– checks, matches, filtering… to properly make sense of, especially, since such process deal with both structured (i.e., stats, figures, databases…) and unstructured data (i.e., social media, email, texting…).

The benefits of filtering and making sense of all of this is huge, and when done properly, the data can spot– major trends, improve efficiency, reduce costs, streamline services and ultimately benefit the companies-people it affects. Of course, this doesn’t mean that you can solely rely on data to improve your fortunes; you need a viable strategy that uses information/data efficiently…

The promise of Big Data is to help companies innovate beyond– the competitors, reduce costs, grow revenue, circumvent risk– and become more agile. According to Shehan Mashood; the problem is complexities of integrating Big Data into business is about as complex as the data itself…

To truly integrate Big Data into an organization there needs to be a ‘data comes first’ ethos instilled in the company… The key is developing ‘use’ cases that prove the effectiveness of Big Data, as well as; its complete integration into the core of the business…

According to Laura Madsen; the reality is that Big Data has always existed; we just didn’t have a term for it. It was all the data we had that we didn’t know what to do with. Yes, it feels like we are all producing a zettabyte of data every time we breathe, but why should that matter? What’s different now? How do we use Big Data?  The key seems to be that in order to take real advantage of Big Data, you must invest in people and processes associated with the data; big or small… Even before getting started, you must determine the business value associated with the data.

According to Ray Jenkin; Big Data can also equal to big distraction; as with any data analysis, understanding and clarifying your business goals when working with various data stakeholders and development teams is critical. Keep asking if it addresses the core business challenges… Consider what value you can extract from internal data sources and investigate external data you can use to augment and enrich it… Big Data is more than simply a matter of size; it’s an opportunity to make the business more agile, and answer questions that were previously considered beyond reach…

Clearly, the use of technologies to manage and find business value from data is becoming more mainstream. Most businesses are beginning to see that the volumes of data are an operational asset, rather than an anchor; for example, in a study 93% say; that their company has used data analysis to predict and analyze future business activities, across a wide range of functions…

Also, 84% say; using Big Data has helped them make better business decisions… Increasingly, companies are using data for competitive intelligence. Amidst all hype and challenges, companies clearly see real value and unrealized potential in Big Data.

According to Trevor Hastie; Big Data has perils, to be sure– there is increased risk of ‘false discoveries’… The trouble with seeking a meaningful needle in massive haystacks of data is that ‘many bits of straw look like needles’.

Despite caveats, there is no turning back: Data is in the driver’s seat: It’s there, it’s useful, it’s valuable, and it’s even hip…