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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Welcome to the career field of Business Intelligence. Business Intelligence is a concept that involves a certain level of interaction within an organism, analytically and dynamically, to come to business solutions which implement better, more effective and timely decision making. These solutions are reached by establishing an understanding of the right kinds of user data: what is going well, what is going wrong, taking and monitoring certain actions, previously unknown trends, and patterns, and improved collaboration. When all of this data is taken into account, the entire decision-making process, within a business, will inevitably improve. As an Oracle BI developer, there are specific skills which will drastically make your job easier and results more effective. As time goes on and technology changes, the list is constantly being updated. The following are skills an Oracle Business Intelligence Developer might need to know or learn in 2019.

Communication

When it comes to running a start up, leaders need to make sure that their key players are motivated. This has been seen with many companies. Back in the 1970's it was found with the inspiration and diligence of the late Daniel Nigro when he formed Kleer-Fax. More recently it was seen in David Khasidy, the founder and recently retired president of SunRay Power Management, the most dynamic green energy leader in the US today.

The question is, what is it that great leaders like David Khasidy and Daniel Nigro do that make the difference? How do the most vulnerable companies (start ups) break the mold and become a part of our everyday lives?

It starts with their mission and vision.

Create a Strong Mission and Vision

There are many reasons why start ups fail. For one, they usually lack the capital to last through the lean times. Secondly, they often don't have the tolerance for setbacks that occur. Lastly, they do not have a long-term plan, also called a mission.

When a business has a strong mission, the team knows it and their focus toward their work and service to others within and without the company reflects that. To complement that, the shorter term vision of the company needs to be present as well.

This can even be seen in sole proprietorships with no employees, such as when Brian Pascale started his law practice. His vision was to find justice for his clients while his mission was to build upon a career that had already set precedents in the area of tort law.

As his practice has grown, new staff members can sense the vision and mission he exudes.

Encourage Ownership of Projects and Processes

Start ups need to inspire and motivate their employees because they need to know that they are not only a part of something important, but that their contributions mean something.

What won't happen if they are not there? What contribution do they make, and what are the consequences of them not fulfilling their part of the work?

By encouraging ownership in projects, team members can find that the work they are doing is not only important for the organization, but that they are going to be a big part of what makes it happen. The alternative is that they feel replaceable.

Offer Incentives That Keep the Company Competitive

When team members embrace the mission and vision of the company, and then take ownership for the company's success, they are going to need to be justly rewarded.

This could include flexible schedules (for those who don't need a stringent one), use of an account at a nearby takeout place, or even the potential for ownership as a result of a vesting program.

The incentive everyone is looking for more immediately, though, is cash. When the company takes in more revenue as a result of the efforts of those on the team, rewarding them can go a long way not only in making them feel appreciated, but in encouraging them to bring in more business.

Members of a start up team are usually very talented, and commonly underpaid. However, if they believe they are going somewhere, it will make a big difference.

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Creating an enum in Python prior to Python 3.4 was accomplished as follows:

def enum(**enums)::
      return type('Enum',(),enums)

then use as:

Animals=enum(Dog=1,Cat=2)

and accessed as:

Animals.Dog

The new version can be created as follows:

from enum import Enum

class Animal(Enum):
    Dog=1
    Cat=2