 |
| YES. I KNOW. IT'S A SMALL PICTURE FOR BIG DATA. If you'll click on it, you'll see the Enterprise-Quality Version. |
"Big Data" is a pop-culture office tech-speak term which refers to any aspect of business which involves handling:
1) a large physical quantity of data input and storage (requiring a great deal of capacity);
2) data derived from a variety of collection or reporting mechanisms which must be translated, sorted, indexed, selectively bundled and rendered navigable;
3) data which must be "mined" or processed in some way such that it can yield information which is most useful to the business or other organization;
Most significantly, is that the notion of aggregating and using increasing amounts of data from increasing sources will accelerate the conversion of a vast number of small- to medium-sized businesses to abandon their overworked systems and outdated software and analytic tools, and instead, link up to the cloud, where storage capacity, data manipulation ability, info-metric analysis and utilization (in terms of obtaining meaningful actionable statistics or trends).
This also bodes well for intelligent CIOs, and CTOs who know how to effect the conversion to cloud-based computing, as well as those Business Strategists and Project Managers who are able to ;everage this colossally large mechanism to produce crucial tactical and strategic information about various aspects of their respective businesses.
Wikipedia contains a brief definition and discussion regarding Big Data and its implications, but I would caution the reader to bear in mind that the prevalence and prominence of big data aggregates, combined with the inevitable vertical spiking curve toward the increasing acceptance and utilization of cloud-based computing by significant industry influencers is rapidly rending this information stale. The topic is extraordinarily dynamic:
In information technology, big data is a collection of data sets so large and complex that it becomes awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analysis, and visualization.
The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions."
Though a moving target, as of 2008, limits were on the order of petabytes to exabytes of data. Scientists regularly encounter limitations due to large data sets in many areas, including meteorology, genomics, connectomics, complex physics simulations, and biological and environmental research.
The limitations also affect Internet search, finance and business informatics. Data sets grow in size in part because they are increasingly being gathered by ubiquitous information-sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, radio-frequency identification readers, and wireless sensor networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012, every day 2.5 quintillion (2.5×1018) bytes of data were created.
Big Data is difficult to work with using relational databases and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers".
What is considered "big data" varies depending on the capabilities of the organization managing the set. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."
--------------
PC Magazine's Encyclopedia has a simpler, more fluid-sounding definition of Big Data for those of you who want to appear intelligent and informed during those early-morning meetings at work when the rest of your colleagues (some of whom may not actually be subscribed to this blog!) are slurping coffee, wiping their bloodshot eyes with baby-like bundled fists, and stifling multiple yawns utilizing the time-honored, but ineffective nostril flaring technique, ensuring that you'll be the only one considered for that big promotion [perhaps I've gone too far with this tangential story]:
Definition of: Big Data
Refers to the massive amounts of data that collect over time that are difficult to analyze and handle using common database management tools. Big data may be any type, such as business transactions, photos or surveillance videos. Scientific research data from logs and sensors can reach mammoth proportions over time, and big data also includes unstructured text posted on the Web, such as blogs and social media.
Big Data Storage and Big Data Analytics
The storage industry is continuously challenged as big data increases exponentially. However, storage can be enhanced with more terabyte drive arrays and more sophisticated indexing methods. The greater challenge is being able to derive meaningful information from data in petabyte and exabyte volumes. Big data analytics break down the data sets into smaller chunks for efficient processing and employ massively parallel computers (see MPP) to derive intelligence for effective decision-making.
---------------
IDG CONNECT Articles and Downloads follow for your further reference regarding Big Data, its probable future, its risks (and guarding against them), benefits (how to "harness the wave" to your organization's ultimate advantage), and more:
| The big data trend has really taken off recently, but some say it's actually the third wave of data insight and intelligence, and there could be more to come. This week's Global Roundup newsletter looks at the truth behind big data and can help you get the most out of business intelligence. Take a look at our latest blog and read reports on big data and BI, then have your say by taking our quick poll. | |||||||||||||||
| Analytics: Why Big Data is Just Another Brick in the Wall | |||||||||||||||
| Every smart business is aware of the big data trend, but is it really anything new? In this blog post, Roel Castelein suggests that big data is the third wave in a sea of analytic trends businesses have seen in recent years. Read it now and find out how big data follows data warehousing and business intelligence, and what new benefits big data really has to offer. | |||||||||||||||
 | |||||||||||||||
| Big Data: How to Fast Forward to the Benefits | |||||||||||||||
| There's a lot of buzz about how big data will transform your business with diagnostics and dashboards distributed directly to business users. The truth is someday big data will do just that… if your organization can clear a few hurdles in getting it under control. This white paper aims to reveal the truths about big data in your organization and unravel the myths behind what big data is and the management solutions that will work to unlock its value. Read on to find out more. | |||||||||||||||
| |||||||||||||||
| Business Intelligence: Why it's Not Time to Overlook BI | |||||||||||||||
| The big data trend is derived from business intelligence, which has been a hot topic among companies for some time now. However, business intelligence is still evolving and is merging with Web 2.0 technologies to become more collaborative. This white paper explains how to take advantage of this. Download now and learn how to get the most out of modern business intelligence. | |||||||||||||||
 | |||||||||||||||
What Big Data means to your company is that you are going to find a way to get used to the idea of cloud computing if you want to compete with other businesses in your industry or market sector. I know -- this is a dangerous dependency and requires carrying a great deal of expensive but outmoded data-handling and computing equipment to the curb.
But the cloud has a silver lining:
It has the benefit of leveling the playing field a bit between the larger companies and the smaller companies in terms of their ability to access and utilize data derived from a variety of sources (mobile phone apps being the largest growing source of input and communication of data). It represents instant scalability...or put more precisely, virtuously continuous scalability without making costlier (and less justifiable) investments in in-office technology.
As Big Data drives more and more business decisions through its endlessly scalable and expandable reformulation of data mining technologies, smaller and medium-sized businesses (SMEs) are going to be able (at least from the standpoint of actionable informatics) to compete with their much larger, much wealthier counterparts.
On a cautionary note, there are still the issues of data security and integrity, as well as the technical issues of concerning the operational uptime and other critical efficiencies of using software as a service, and working with the faceless robodenizens inhabiting a non-physical safe house somewhere in deep cyberspace.
Be extremely careful in choosing your cloud services provider, and be certain to have ample resources to back up critical information in the event of a data disaster in a data center that you cannot even physically visit as a source of tangible comfort.
---------------
Douglas E. Castle for The Business And Project Planning And Management Blog and The Daily Burst Of Brilliance Blog [which is only occasionally brilliant -- to be fully candid -- and which is actually not daily at all...a good article or chunk of commentary gets published and syndicated perhaps two to three times per month].
No comments:
Post a Comment