Big data is now in an incredibly important part of how many major businesses function. Data analysis, or the finding of facts from large volumes of data, helps businesses make many of their important decisions. Companies that conduct business on a national or international scale rely on big data in order to plot the general direction of their business. The concept of big data can be very confusing due to the sheer scale of information involved.  By following a few simple guidelines, even the layman can understand big data and its impacts on everyday life.

What Exactly is Big Data?

Just about everyone can understand the concept of data. Data is information, and information is everywhere in the modern world. Anytime you use any piece of technology you are making use of data. Anytime you read a book, skim the newspaper or listen to music you are also making use of data. Your brain interprets and organizes data constantly from your senses and your thoughts.

Big data, much like its name infers, simply describes this same data on a large sale. The internet allowed the streaming, sharing and collecting of data on a scale never before imaginable and storage technology has allowed ever increasing hoards of data to be accumulated. In order for something to be considered “big data” it must be at least 10 terabytes or more of information. To put that in perspective, consider that 10 terabytes represents the entire printed collection of material in the Library of Congress. What’s even more remarkable is that many businesses work with far more than the minimum 10 terabytes of data. UPS stores over 16 petabytes of data about its packages and customers. That’s 16,000 terabytes or the equivalent to 1,600 printed libraries of congress. The sheer amount of that data is nearly impossible for a human to comprehend, and analysis of this data is only possible with computers.

How do Big Data Companies Emerge?

All of this information comes from everywhere on the internet. The majority of the useful data includes customer information, search engine logs, and entries on social media networks to name a few. This data is constantly generated by the internet at insane rates. Specified computers and software programs are created and operated by big data companies that collect and sort this information. These programs and hardware are so sophisticated and so specialized that entire companies can be dedicated to analyzing this data and then selling it to other companies. The raw data is distilled down into manageable reports that company executives can make use of when handling business decisions.

The Top Five:

These are the five biggest companies, according to Forbes, in the business of selling either raw data reports or analytics programs that help companies to compile their own reports.

1. Splunk
Splunk is currently valued at $186 million.  It is essentially a program service that allows companies to turn their own raw data collections into usable information.

2. Opera Solutions
Opera Solutions is valued at $118 million. It serves as a data science service that helps other companies to manage the raw data that pertains to them. They can offer either direct consultation or cloud-based service.

3. Mu Sigma
Mu Sigma is valued at $114 million.  It is a slightly smaller version of Opera Solutions, offering essentially the same types of services.

4. Palantir
Palantir is valued at $78 million.  It offers data analysis software to companies so they can manage their own raw data analysis.

5. Cloudera
Cloudera is valued at $61 million.  It offers services, software and training specifically related to the Apahce Hadoop-based programs.

The software and services provided by these companies impact nearly all major businesses, industries and products. They impact what business offer, where they offer them and how they advertise them to consumers. Every advertisement, new store opening or creation of a new product is at least somewhat related to big data analysis. It is the directional force of modern business.

Sources:
http://www.sas.com/en_us/insights/big-data/what-is-big-data.html

http://www.forbes.com/sites/gilpress/2013/02/22/top-ten-big-data-pure-plays/

http://www.whatsabyte.com/

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When eCommerce companies want to optimize information security, password management tools enable users to create strong passwords for every login.

Better than a Master Pass
A two-factor authentication, a security process in which the user provides two means of identification, one of which is typically a physical token, such as a card, and the other of which is typically something memorized, such as a security code can drastically reduce online fraud such as identity theft . A common example of two-factor authenticationis a bank card: the card itself is the physical item and the personal identification number (PIN) is the data that goes with it.

LastPass 3.0 Premium and RoboForm, security downloads offer fingerprint-based authentication features that can be configured to any computer PC or mobile application.  Both are supported by the Google Authenticator mobile app for smart phone and device integration.

LastPass 3.0 is most powerful on-demand password manager on the market. LastPass 3.0 Premium includes mobile support and more features. Dashlane 2.0 is is not as robust, but includes a user-friendly interface. F-Secure Key is a free, one-device version of these top competitors. F-Secure Key is for exclusive use on an installed device, so password safe retention is dependent on proprietary use of the device itself. The application can be upgraded for a small annual fee.

Password Manager App Cross-Portability
F-Secure Key syncs with Mac, PC Android, and iOS devices simultaneously. A transient code is generated on mobile devices, in addition to the two-factor authentication default of the F-Secure Key master password security product.

Password capture and replay in case of lost credentials is made possible with a password manager. Integration of a password manager app with a browser allows a user to capture login credentials, and replay on revisit to a site. Dashlane, LastPass, Norton Identity Safe, Password Genie 4.0 offer continuous detection and management of password change events, automatically capturing credentials each time a new Web-based, service registration sign up is completed.

Other applications like F-Secure Key, KeePass, and My1login replay passwords via a bookmarklet, supported by any Java-equipped browser. KeePass ups the ante for would be keyloggers, with a unique replay technology.

Personal Data and Auto-Fill Forms
Most password managers fill username and password credentials into login forms automatically. Password managers also retain personal data for form fill interfaces with applications, and other HTML forms online. The RoboForm app is one of the most popular for its flexibility in multi-form password and personal data management, but the others also capture and reuse at least a portion of what has been entered in a form manually.

The 1Password app for Windows stores the most types of personal data for use to fill out forms. Dashlane, LastPass, and Password Genie store the various types of ID data used for form fill-in, like passport and driver's license numbers and other key details to HTML acknowledgement of discretionary password and personal information.

The Cost of Protection
LastPass Premium and Password Box are the lowest monthly password manager plans on the market, going for $1 a month. Annual plans offered by other password manager sources vary according to internal plan: Dashlane $20, F-Secure Key $16, and Password Genie, $15.
All password manager companies and their products may not be alike in the end.

Security checks on security products like password managers have become more sophisticated in response to product cross-portability and open source app interface volatility. Norton, RoboForm, KeePass, generate strong, random passwords on-demand. Some security procedures now require three-factor authentication, which involves possession of a physical token and a password, used in conjunction with biometricdata, such as finger-scanningor a voiceprint.

What are the best languages for getting into functional programming?

Computer Programming as a Career?

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Once again Java tops C as the number one sought after programming language on the internet.  According TIOBE Programming Community Index for February 2013 and five search engines: Google, Bing, Yahoo!, Wikipedia, Amazon, YouTube and Baidu, Java regained its position after being bumped by C in May 2012.

Despite the recent urging by the U.S. Department of Homeland Security of computer users to disable or uninstall Java due to a flaw in Runtime Environment (JRE) 7, Java, has increased its market share of all languages by (+2.03%) in the past six months. The jump in Java’s popularity does not come as a surprise as the Android OS claims massive success in the mobile space.  The top twelve programming languages listed in the index are:

1.  Java
2.  C
3.  Objective-C 
4.  C++
5.  C#
6.  PHP
7.  Python
8.  (Visual) Basic
9.  Perl
10.  Ruby
11. Java Script
12. Visual Basic.NET

Also rising, Python and PHP which are competing to becoming the most popular interpreted language.