All about Big Data

Before Understand What is Big data,Please know What Happens in an Internet Minute

What Happens in an Internet Minute?

Terabytes, Petabytes, Exabytes.  Who can keep track?  These strange terms have just begun to enter the business lexicon, but the hype surrounding them has reached a fever pitch.  We have undoubtedly entered the age of big data.

1.What is Big Data?

1.1.Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.
 

Big Data Explained

1.2.Big data is not just about the size of the data. Well… yes it is data and it is big but it’s not all about the size of the data. Big data is about the pace at which the data is generated and the complexity of the attributes it carries. For example, the data could be in all sorts of data types i.e. tables, documents, chat logs, blog postings, videos, and formats i.e. html, .doc, .pdf, .txt, .ppt, etc., from various sources, and produced in different languages and styles.

 

2.Where is it come from?

The data, that is loosely classified as big data, is mainly user-generated content through various online platforms such as web media, social media, blogs, video blogs, and through offline daily interactions such as smart cards, credit card purchases, points cards (membership or discount cards), interactive point of sale machines (iPOS), and bar code scanners. This data is left behind by various end-users such as businesses, educational institutions, healthcare and scientific institutions, and of course individuals like us

3.Why use Big Data?

Like Google says: “Know the user. Know the magic. Connect the two.” and yes that is when you are able to do cool stuff that can impact people’s lives. When you combine online data with offline data, it paints the whole picture of your target industry trends. What does these trends and analysis tells us? We can benefit from them by finding shifting and emerging trends in the industry and customer behaviour patterns, purchase habits, declining sales and shares value, and adapt our business strategy accordingly. It helps us optimize customer interactions and put the right product in front of the right customer in the right time.

Marketers can use big data analysis for informed decision making such as customer profiling, behaviour analysis, RMF analysis (recencey, frequency and monetary value of customers), and predicting trends, sales, and customer behaviour.

According to IBM data analytics helps us “provide customized intelligence to gain faster insight” from the information we have. We can predict outcomes and financial trends by “turning information into insight and developing conclusive, fact based strategies to gain that competitive edge.”

4.Three V's of  Big Data?

Big Data relates to data creation, storage, retrieval and analysis that is remarkable in terms of volume, velocity, and variety:

Three V's Of Big Data

• Volume. A typical PC might have had 10 gigabytes of storage in 2000. Today, Facebook ingests 500 terabytes of new data every day; a Boeing 737 will generate 240 terabytes of flight data during a single flight across the US; the proliferation of smart phones, the data they create and consume; sensors embedded into everyday objects will soon result in billions of new, constantly-updated data feeds containing environmental, location, and other information, including video.
• Velocity. Clickstreams and ad impressions capture user behavior at millions of events per second; high-frequency stock trading algorithms reflect market changes within microseconds; machine to machine processes exchange data between billions of devices; infrastructure and sensors generate massive log data in real-time; on-line gaming systems support millions of concurrent users, each producing multiple inputs per second.
• Variety. Big Data data isn't just numbers, dates, and strings. Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media.
  Traditional database systems were designed to address smaller volumes of structured data, fewer updates or a predictable, consistent data structure. Traditional database systems are also designed to operate on a single server, making increased capacity expensive and finite. As applications have evolved to serve large volumes of users, and as application development practices have become agile, the traditional use of the relational database has become a liability for many companies rather than an enabling factor in their business. 

5.Types of Data Big Data Handles.

1.Structured Data

Structured data first depends on creating a data model – a model of the types of business data that will be recorded and how they will be stored, processed and accessed. This includes defining what fields of data will be stored and how that data will be stored: data type (numeric, currency, alphabetic, name, date, address) and any restrictions on the data input (number of characters; restricted to certain terms such as Mr., Ms. or Dr.; M or F).

Structured data has the advantage of being easily entered, stored, queried and analyzed. At one time, because of the high cost and performance limitations of storage, memory and processing, relational databases and spreadsheets using structured data were the only way to effectively manage data. Anything that couldn't fit into a tightly organized structure would have to be stored on paper in a filing cabinet.

2.Unstructured and Semi-Structured Data

Unstructured data is all those things that can't be so readily classified and fit into a neat box: photos and graphic images, videos, streaming instrument data, webpages, PDF files, PowerPoint presentations, emails, blog entries, wikis and word processing documents.

Semi-structured data is a cross between the two. It is a type of structured data, but lacks the strict data model structure. With semi-structured data, tags or other types of markers are used to identify certain elements within the data, but the data doesn't have a rigid structure. For example, word processing software now can include metadata showing the author's name and the date created, with the bulk of the document just being unstructured text. Emails have the sender, recipient, date, time and other fixed fields added to the unstructured data of the email message content and any attachments. Photos or other graphics can be tagged with keywords such as the creator, date, location and keywords, making it possible to organize and locate graphics. XML and other markup languages are often used to manage semi-structured data.

3.Multi Structured Data

Multi-structured data refers to a variety of data formats and types and can be derived from interactions between people and machines, such as web applications or social networks. A great example is web log data, which includes a combination of text and visual images along with structured data like form or transnational information.As digital disruption transforms communication and interaction channels—and as marketers enhance the customer experience across devices, web properties, face-to-face interactions and social platforms—multi-structured data will continue to evolve.

Example Application of Type of data Big Data Handles.

1.       Web and social media

This includes clickstream and social media data such as Facebook, Twitter, LinkedIn, and blogs. Big data governance programs will increasingly be required to integrate this data with master data and with core business processes such as customer loyalty programs. The big data governance program needs to establish policies regarding the acceptable use of social media data especially as regulations and precedents are continually evolving. The program also needs to establish guidelines regarding the acceptable use of cookies, especially third-party cookies, to track users and to personalize their web interactions. Metadata is also critical to web and social media. For example, two sites may measure the term “unique visitors” differently for clickstream analytics. One site may measure unique visitors within a month while another one may measure unique visitors within a week.

2.       Machine-to-machine data

Machine-to-machine (M2M) refers to technologies that allow both wireless and wired systems to communicate with other devices. M2M uses a device such as a sensor or meter to capture an event (such as speed, temperature, pressure, flow, or salinity) which is relayed through a wireless, wired, or hybrid network to an application that translates the captured event into meaningful information. M2M communications create the so-called “internet of things.” The big data governance program needs to establish a number of policies around M2M data. For example, the program needs to draw up guidelines around the acceptable use of geolocation and RFID data that can be used to build a profile of individuals and potentially violate their privacy. The program also needs to establish retention policies around the massive volumes of M2M data that can easily overwhelm IT budgets if not properly controlled. The big data governance program also needs to address any data quality concerns such as RFID read rates in environments with high moisture content and lots of congestion.

3.       Big transaction data

This includes healthcare claims, telecommunications call detail records, and utility billing records. Big transaction data is increasingly available in semi-structured and unstructured formats. Information governance challenges such as metadata, data quality, privacy, and information lifecycle management also apply to this data.

4.       Biometrics

Biometric information includes fingerprints, retinal scans, facial recognition, and genetics. Advances in technology have vastly increased the available biometric data. Law enforcement, the legal system, and intelligence agencies have been using this information for a long time. However, biometric data is increasingly available in the commercial arena where it can be co-mingled with other types of data such as social media. For example, page 45 of the attached FTC report describes a scenario where retailers can combine facial recognition with social media to personalize messages to customers.

5.      Human generated data

Human beings generate vast quantities of data such as call center agents’ notes, voice recordings, email, paper documents, surveys, and electronic medical records. This data may contain sensitive information that needs to be masked. It may contain insights that can improve the quality of structured data sets and should be integrated with MDM. Finally, organizations need to establish policies regarding the retention period for this data to adhere to regulations and to manage storage costs.

How to get Jobs in Singapore

1. Work in Singapore

If you are a senior talent who meets the below requirements,
you can consider applying for the Personalised Employment Pass
Personalised Employment Pass (PEP)

• Overseas applicants should have a minimally last drawn
  monthly salary of S$18,000 or hold a skilled migrant visa.
• The PEP is not tied to a specific employer and is granted on the
  strength of an EP holder's individual merits. It also allows the
  holder to remain in Singapore for up to six months in
  between jobs

2. Search Jobs

Job Search Channels

• Contact Singapore's Job Portal, Jobs@Singapore
• Career & networking events organised by Contact Singapore
• E-mailers sent by Contact Singapore. 
• Job sites
• Potential employers' websites
• Headhunters & recruiting firms
• Referral from friends/family
• The Recruit section of Singapore's The Straits Times
  Saturday edition
• Networking is one of the most effective methods of meeting
  potential employers. You may like to print a set of personal
  name cards for such events.

 3. Prepare Perfect Resume

Prepare your resume

• Send your resume and job application together
• Provide supporting documents (such as school certificates
  and testimonials) or demo reels (if you are in the creative industry)
• Most employers accept resumes via email

Tips on preparing your CVs

• Keep your resume short (about 2-3 pages)
  and succinct.
• List your relevant work experience and educational
  qualifications, starting with the most recent
• Put your most important skills at the beginning

4.Interview Process

• Most employers only inform candidates if they are
  shortlisted for an interview
• The interview process differs from employer to
  employer and ranges from 2 weeks to 2-3 months
• If you are currently overseas, employers may
  interview you over the phone or video conference,
  or their local office may conduct the interview
• Some employers may require candidates to
  prepare an essay or presentation
• Employers in Singapore usually look for:

-	Qualifications
-	Ability to adapt
-	International outlook
-	Basic English etc.

5.Accepting Jobs

• Deciding whether to take up the job will
  be one of the most important decisions
  you'll be making
• Most employers will require you to sign
  an employment contract upon acceptance
  of the job
• The contract will lay out the terms of your
  employment including your salary,
  bonuses, working hours, etc
• You will usually be given 2-5 days to go
  through the terms before you need to sign
  the contract 

6.Apply for Work Visa

• Non-Singapore citizens and Permanent Residents will
  need an Employment Pass (EP) to work in Singapore
• Mid-skilled non-citizens may apply for the S Pass
• Application of work visas are done by the employer
• Application can be done online or manually

 7.Approval of your work visa

• Your employer will receive an In-Principle Approval
  (IPA) letter upon approval of your Employment
  Pass (EP) or S Pass
• The IPA letter must be produced upon collection
  of the EP or S Pass from the Ministry of Manpower
  Work Pass Division
• The IPA letter is valid for six months from the date
  of the letter
• You can collect your EP / S Pass from the Employment
  Pass Service Centre (EPSC) only after you arrive
  in Singapore
• Validity is up to two years for first-time applicants
  and up to three years for EP / S Pass renewals

8.Relocating to Singapore is hassle-free

• You may choose to engage a relocation company or take care of the relocation yourself
• Things to look out for:

-	Housing	-	Healthcare	-	Transportation
-	Children's Education	-	Banking Services	-	Communication

• Contact Singapore holds welcome sessions for those who are planning
  to relocate to Singapore

        Apply for PR and Citizenship

• Holders of an EP or S Pass can apply for Permanent
  Residence under the Professionals/Technical
  Personnel and Skilled Workers Scheme. It takes
  at least 6 months to process the application
• If you are a PR, you can sponsor your spouse
  and unmarried children below 21 years old to apply
  for PR
• You can apply for citizenship if you are above 21 years
  of age and have spent 2 years as a PR in Singapore
• All applications are subject to the approval
  of the Immigration and Checkpoints Authority

Job Title: Tier 1 Customer Support Executive

Job Title: Tier 1 Customer Support Executive

Job Location: Chennai

General Description: Customer Support Executive for the company's family of Antivirus-products. Candidate will possess a broad knowledge on handling customer calls. Candidate will be highly experienced in providing excellent customer service and problem escalation/resolution.
Primary Job Functions:

• Conduct B/G verification of all registered partners
• Proactively contact channel partners to communicate schemes/offers
• Following up channel partners on scheme performance.
• Communicate new product launch to all customer through calls & other modes.
• Create a personalized engagement with channel partner to enhance business relationship.
• Conduct & collect feedback on Product/ Services/ schemes etc.
• Promote new schemes and upselling of new product lines.
• Work closely with supporting functions to address any grievances reported by the channel.
• Report regularly to team leader on all activities relating to the role
• Achieve Daily Contact targets as specified in KRA
• Effective and prompt customer support measures & coordination with Support Team
• Maintain 100% accurate MIS for various business analytics.
• Identify new business practices , suggest modifications to existing practices on business.
• Derive knowledge on products and services in order to understand customers’ needs

Required Skills:

• Prior Calling Experience with customer/ business partner
• Confident and enthusiastic customer Service Attitude.
• Preferred Languages to be known- HINDI,ENGLISH,TAMIL,TELUGU,MALYALAM.BENGALI
• Consultative selling and Negotiation Skills
• Attention to detail and accuracy.
• Excellent verbal and written communication skills.
• Excellent telephone manner.
• Ability to work in shifts and on weekends.

Desired Skills: Experience in handling customer service and providing technical support over phone, email or live chat.

Experience: 0-1 year of experience in any support/help desk environment.

Education: Any UG

Work Status: Full time

Travel: Position requires 0% travel.

Reporting: Reports to the Senior Manager of Contact Center

**To Apply for this position kindly send your resume to hr@k7computing.com

The Great Lord Buddha Message About "You let it be".

Once Buddha was traveling with a few of his followers.

While they were passing a lake, Buddha told one of his disciples, "I am thirsty. Do get me some water from the lake."The disciple walked up to the lake.
At that moment, a bullock cart started crossing through the lake. As a result, the water became very muddy and turbid.The disciple thought, "How can I give this muddy water to Buddha to drink?"

So he came back and told Buddha, "The water in there is very muddy. I don't think it is fit to drink."

After about half an hour, again Buddha asked the same disciple to go back to the lake.

The disciple went back, and found that the water was still muddy.He returned and informed Buddha about the same.After sometime, again Buddha asked the same disciple to go back.This time, the disciple found the mud had settled down, and the water was clean and clear.So he collected some water in a pot and brought it to Buddha.Buddha looked at the water, and then he looked up at the disciple and said,  

"See what you did to make the water clean. You let it be, and the mud settled down on its own, and you have clear water."Your mind is like that too ! When it is disturbed, just let it be. Give it a little time. It will settle down on its own.You don't have to put in any effort to calm it down. It will happen. It is effortless."

Having 'Peace of Mind' is not a strenuous job, it is an effortless process.keep ur mind cool and have a great life ahead...Never leave Your close ones. If you find few faults in them just close Your eyes 'n Remember the best time You spent together because affection is More Important than Perfection..! Neither you can hug yourself nor you can cry on your own shoulder.Life is all about living for one another, so live with those who love you the most...

Relations cannot be Understood by the Language of Money...
Because, Some Investments Never Give Profit But They Make us rich...!

"Family n Friends are such Investments"

The Secret - It can change your life.Think,Visualize and Get it.

 Change your life with "THE POWER YOU HAVE" 

 

The Secret. It has been passed throughout the ages, traveling through centuries… to reach you. This is the secret to everything – joy, health, money, relationships, love, happiness… everything you have ever wanted. In this astonishing film are ALL the resources you will need to understand and live The Secret. For the first time in history leading scientists, authors, and philosophers will reveal The Secret, a secret that utterly transformed the lives of those who lived it… Plato, Newton, Carnegie, Beethoven, Shakespeare, Einstein. Now YOU will know The Secret, and it can change your life forever.

 

 

 

Thoughts become things.

Who am I ?. The video about who you are?

This film deals with Journey that takes you to the eternal truth, for which from time immemorial, people have been trying to explore and discover a simple truth to understand the self, Karma & Rajyoga Meditation.

Tamil Video

 

 English Video

What is Database?

A database is a systematic collection of data. Databases support storage and  manipulation of data. Databases make data management easy. Let's discuss few examples.
An online telephone directory would definitely use database to store data pertaining to people, phone numbers, other contact details, etc.
Your electricity service provider is obviously using a database to manage billing , client related issues, to handle fault data, etc.
Let's also consider the facebook. It needs to store, manipulate and present data related to members, their friends, member activities, messages, advertisements and lot more.
We can provide countless number of examples for usage of databases .

What is a Database Management System (DBMS)

Database Management System (DBMS) is a collection of programs which enables its users to access database, manipulate data, reporting / representation of  data . It also helps to control access to the  database.
Database Management Systems are not a new concept and as such had been first implemented in 1960s. Charles Bachmen's Integrated Data Store(IDS) is said to be the first DBMS in history. With time database technologies evolved a lot while usage and expected functionalities of databases have been increased immensely.

Types of DBMS

Let's see how the DBMS family got evolved with the time. Following diagram shows the evolution of DBMS categories.

There are 4 major types of DBMS. Let's look into them in detail.

• Hierarchical - this type of DBMS employs the "parent-child" relationship of storing data. This type of DBMS is rarely used nowadays. Its structure is like a tree with nodes representing records and branches representing fields. The windows registry used in Windows XP is an example of a hierarchical database. Configuration settings are stored as tree structures with nodes.
• Network DBMS - this type of DBMS supports many-to many relations. This usually results in complex database structures.  RDM Server is an example of a database management system that implements the network model.
• Relational DBMS - this type of DBMS defines database relationships in form of tables, also known as relations. Unlike network DBMS, RDBMS does not support many to many relationships.Relational DBMS usually have pre-defined data types that they can support. This is the most popular DBMS type in the market. Examples of relational database management systems include MySQL, Oracle, and Microsoft SQL Server.
• Object Oriented Relation DBMS - this type supports storage of new data types. The data to be stored is in form of objects. The objects to be stored in the database have attributes (i.e. gender, ager) and methods that define what to do with the data. PostgreSQL is an example of an object oriented relational DBMS.

 
1.What is Structured Query language (SOL)




Structured Query language (SQL) pronounced as "S-Q-L" or sometimes as "See-Quel"is actually the standard language for dealing with Relational Databases. SQL can be effectively used to insert, search, update, delete database records. That doesn't mean SQL cannot do things beyond that. In fact it can do lot of things including, but not limited to ,optimizing and maintenance of databases.  Relational databases like MySQL, Oracle, Ms SQL server, Sybase, etc uses SQL !  SQL syntaxes used in these databases are almost similar, except the fact that some are using few different syntaxes and even proprietary SQL syntaxes.

What is NoSQL ?

NoSQL is an upcoming category of Database Management Systems..Its main characteristic is its non-adherence to Relational Database Concepts. NOSQL means "Not only SQL".
Concept of NoSQL databases grew with internet giants such as Google, Facebook, Amazon etc who deal with gigantic volumes of data.When you use relational database for massive volumes of data , the system starts getting slow in terms of response time. To overcome this , we could of course "scale up" our systems by upgrading our existing hardware. The alternative to the above problem would be to distribute our database load on multiple hosts as the load increases. This is known as "scaling out".
 NOSQL database are non-relational databases that scale out better than relational databases and are designed with web applications in mind. They do not use SQL to query the data and do not follow strict schemas like relational models.With NoSQL, ACID (Atomicity, Consistency, Isolation, Durability) features are not guaranteed always.

Relational databases have the following advantages over NOSQL databases;

• SQL(relational) databases have a mature data storage and management model . This is crucial for enterprise users.
• SQL databases support the notion of views which allow users to only see data that they are authorized to view. The data that they are not authorized to see is kept hidden from them.
• SQL databases support stored procedures which allow database developers to implement part of the business logic into the database.
• SQL databases have better security models compared to NoSQL databases.

What is Normalization?

Normalization is a database design technique which organizes tables in a manner that reduces redundancy and dependency of data.
It divides larger tables to smaller tables and link them using relationships.
The inventor of the relational model Edgar Codd proposed the theory of normalization with the introduction of First Normal Form and he continued to extend theory with Second and Third Normal Form. Later he joined with Raymond F. Boyce  to develop the theory of Boyce-Codd Normal Form.
Theory of Normalization is still being developed further. For example there are discussions even on 6^th Normal Form. But in most practical applications normalization achieves its best in 3^rd Normal Form. The evolution of Normalization theories is illustrated below-

Let's learn Normalization with practical example -
Assume a video library maintains a database of movies rented out. Without any normalization all information is stored in one table as shown below.

Table 1

Here you see Movies  Rented column has multiple values.
Now let's move in to 1^st Normal Form

1NF Rules

• Each table cell should contain single value.
• Each record needs to be unique.

The above table in 1NF-

Table 1 : In 1NF Form

Before we proceed lets understand a few things --

What is a KEY ?

A KEY  is a value used to uniquely identify a record in a table. A KEY could be a single column or combination of multiple columns
Note: Columns in a table that are NOT used to uniquely identify a record are called non-key columns.

What is a primary Key?

A primary is a single column values used to uniquely identify a database record. It has following attributes A primary key cannot be NULL A primary key value must be unique The primary key values can not be changed The primary key must be given a value when a new record is inserted.

What is a composite Key?

A composite key is a primary key composed of multiple columns used to identify a record uniquely
In our database , we have two people with the same name Robert Phil but they live at different places.

Hence we require both Full Name and Address to uniquely identify a record. This is a composite key.
Let's move into 2NF
2NF Rules

• Rule 1- Be in 1NF
• Rule 2- Single Column Primary Key

It is clear that we can't move forward to make our simple database in 2^nd Normalization form unless we partition the table above.

Table 1

Table 2

We have divided our 1NF table into two tables viz. Table 1 and Table2. Table 1 contains member information. Table 2 contains information on movies rented.
We have introduced a new column called Membership_id which is the primary key for table 1. Records can be uniquely identified in Table 1 using membership id

Introducing Foreign Key!

In Table 2, Membership_ID is the foreign Key

Foreign Key references primary key of another Table!It helps connect your Tables A foreign key can have a different name from its primary key It ensures rows in one table have corresponding rows in another Unlike Primary key they do not have to be unique. Most often they aren't Foreign keys can be null even though primary keys can not

Why do you need a foreign key ?
Suppose an idiot inserts a record in Table B such as
You will only be able to insert values into your foreign key that exist in the unique key in the parent table. This helps in referential integrity.

The above problem can be overcome by declaring membership id  from Table2  as foreign key of membership id  from Table1
Now , if somebody tries to insert a value in the membership id  field that does not exist in the parent table , an error will be shown!

What is a transitive functional dependencies?

A transitive functional dependency is when changing a non-key column , might cause any of the other non-key columns to change
Consider the table 1. Changing the non-key column Full Name , may change Salutation.

Let's move into 3NF

3NF Rules

• Rule 1- Be in 2NF
• Rule 2- Has no transitive functional dependencies

To move our 2NF table into 3NF we again need to need divide our table.

TABLE 1

Table 2

Table 3

We have again divided our tables and created a new table which stores Salutations.
There are no transitive functional dependencies and hence our table is in 3NF
In Table 3 Salutation ID is primary key and in Table 1 Salutation ID is foreign to primary key in Table 3
Now our little example is in a level that cannot further be decomposed to attain higher forms of normalization. In fact it is already in higher normalization forms. Separate efforts for moving in to next levels of normalization are normally needed in complex databases.  However we will be discussing about next levels of normalizations in brief in the following.

Boyce-Codd Normal Form (BCNF)

Even when a database is in 3^rd Normal Form, still there would be anomalies resulted if it has more than one Candidate Key.
Sometimes is BCNF is also referred as 3.5 Normal Form.

4^th  Normal Form

If no database table instance contains two or more, independent and multivalued data describing the relevant entity , then it is in 4^th Normal Form.

5^th  Normal Form

A table is in 5^th Normal Form only if it is in 4NF and it cannot be decomposed in to any number of smaller tables without loss of data.

6^th  Normal Form

6^th Normal Form is not standardized yet however it is being discussed by database experts for some time. Hopefully we would have clear standardized definition for 6^th Normal Form in near future.

Inspiration from geniuses

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1. Albert Einstein » Physicist
Best known for the General Theory of Relativity.
Most of us take Einstein’s name as synonymous with genius, but he didn’t always show such promise. Einstein did not speak until he was four and did not read until he was seven, causing his teachers and parents to think he was mentally handicapped, slow and anti-social.
Eventually, he was expelled from school and was refused admittance to the Zurich Polytechnic School. It might have taken him a bit longer, but most people would agree that he caught on pretty well in the end, winning the Nobel Prize and changing the face of modern physics.

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2. Walt Disney » Business Man
Founder of The Walt Disney Company.
Today Disney rakes in billions from merchandise, movies and theme parks around the world, but Walt Disney himself had a bit of a rough start. He was fired by a newspaper editor because, “he lacked imagination and had no good ideas.”
After that, Disney started a number of businesses that didn’t last too long and ended with bankruptcy and failure. He kept plugging along, however, and eventually found a recipe for success that worked.

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3. Isaac Newton » Scientist
Best known for: Universal gravitation, Newton’s method,
Newtonian mechanics, Optics, Infinitesimal calculus.
Newton was undoubtedly a genius when it came to math, but he had some failings early on. He never did particularly well in school and when put in charge of running the family farm, he failed miserably, so poorly in fact that an uncle took charge and sent him off to Cambridge where he finally blossomed into the scholar we know today.

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4. Thomas Edison » Inventor and Businessman
Best known for Electric Light Bulb.
In his early years, teachers told Edison he was “too stupid to learn anything.”
Work was no better, as he was fired from his first two jobs for not being productive enough. Even as an inventor, Edison made 1,000 unsuccessful attempts at inventing the light bulb. Of course, all those unsuccessful attempts finally resulted in the design that worked.

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5. Henry Ford » Business Man
Founder of Ford Motor.
While Ford is today known for his innovative assembly line and American-made cars, he wasn’t an instant success. In fact, his early businesses failed and left him broke five times before he founded the successful Ford Motor Company.

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6. Soichiro Honda » Business Man
Founder of Honda Motor.
The billion-dollar business that is Honda began with a series of failures and fortunate turns of luck. Honda was turned down by Toyota Motor Corporation for a job after interviewing for a job as an engineer, leaving him jobless for quite some time.
He started making scooters of his own at home, and spurred on by his neighbors, finally started his own business.

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7. Akio Morita » Business Man
Founder of Sony Corporation.
You may not have heard of Morita but you’ve undoubtedly heard of his company, Sony.
Sony’s first product was a rice cooker that unfortunately didn’t cook rice so much as burn it, selling less than 100 units. This first setback didn’t stop Morita and his partners as they pushed forward to create a multi-billion dollar company.

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8. Orville and Wilbur Wright (Wright Brothers) » Airplane Inventors

Education: Completed High School.
These brothers battled depression and family illness before starting the bicycle shop that would lead them to experimenting with flight.
After numerous attempts at creating flying machines, several years of hard work, and tons of failed prototypes, the brothers finally created a plane that could get airborne and stay there.

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9. Winston Churchill » UK Politician
This Nobel Prize-winning, twice-elected Prime Minster of the United Kingdom wasn’t always as well regarded as he is today.
Churchill struggled in school and failed the sixth grade. After school he faced many years of political failures, as he was defeated in every election for public office until he finally became the Prime Minister at the ripe old age of 62.

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10. Abraham Lincoln » US Politician
While today he is remembered as one of the greatest leaders of our nation, Lincoln’s life wasn’t so easy. In his youth he went to war a captain and returned a private (if you’re not familiar with military ranks, just know that private is as low as it goes.)
Lincoln didn’t stop failing there, however. He started numerous failed business and was defeated in numerous runs he made for public office.

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11. Vincent Van Gogh » Artist
During his lifetime, Van Gogh sold only one painting, and this was to a friend and only for a very small amount of money.
While Van Gogh was never a success during his life, he plugged on with painting, sometimes starving to complete his over 800 known works.

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12. Michael Jordan » Basketball Player
Most people wouldn’t believe that the man often lauded as the best basketball player of all time was actually cut from his high school basketball team.
Luckily, Jordan didn’t let this setback stop him from playing the game and he has stated, “I have missed more than 9,000 shots in my career. I have lost almost 300 games. On 26 occasions I have been entrusted to take the game winning shot, and I missed. I have failed over and over and over again in my life. And that is why I succeed.”

Source from : http://academictips.org/blogs/inspiration-from-top-geniuses/

What is Business Intelligence?

Business Ingelligence (BI) - technology infrastructure for gaining maximum information from available data for the purpose of improving business processes. Typical BI infrastructure components are as follows: software solution for gathering, cleansing, integrating, analyzing and sharing data. Business Intelligence produces analysis and provides believable information to help making effective and high quality business decisions.

The most common kinds of Business Intelligence systems are:

EIS - Executive Information Systems

DSS - Decision Support Systems

MIS - Management Information Systems

GIS - Geographic Information Systems

OLAP - Online Analytical Processing and multidimensional analysis

CRM - Customer Relationship Management

Business Intelligence systems based on Data Warehouse technology. A Data Warehouse(DW) gathers information from a wide range of company's operational systems, Business Intelligence systems based on it. Data loaded to DW is usually good integrated and cleaned that allows to produce credible information which reflected so called 'one version of the true'. 

List of BI tools in the market :

1. SAP BusinessObjects: a complete BI platform
2. IBM Cognos Series 10: strong in analytics
3. JasperSoft: open source, now TIBCO
4. Microsoft BI tools: a complete BI platform
5. MicroStrategy: strong in reporting & performance
6. Oracle BI (OBIEE): a complete BI platform
7. Oracle Hyperion System: tool for consolidation
8. Pentaho BI: open source, now HDS
9. Yellowfin BI: strong in dashboards
10. Qlik: strong in Data Discovery
11. SAP NetWeaver BW: data warehouse + cubes
12. SAS BI: very strong in analytics
13. Style Intelligence: a niche player
14. Tableau Software: strong in Data Visualization
15. WebFOCUS: a complete BI platform
16. BizzScore: strong in performance management
17. Board: strong in performance management
18. Birst: a complete BI platform in the cloud

Flipkart Marketing strategy

Flipkart digital marketing

It’s being touted as India’s answer to Amazon. Founded by Sachin Bansal and Binny Bansal (not related to each other) in Oct 2007, Flipkart has catapulted to one of India’s most popular e-commerce sites and undoubtedly as the most popular online destination for books within a short span of three years. With expected revenues of Rs. 75 crores this FY, Flipkart plans to generate a whopping Rs. 4,500 crores by FY2015. Now that’s pretty impressive for any business.
Flipkart’s initial success can be pegged down to the experience of its founders, both of whom had worked with Amazon. They also successfully used word of mouth marketing and social media to get word out. But there are literally millions of retail websites. And not many have achieved even a fraction of the attention that Flipkart has. So what is it that makes Flipkart stand out? For one, they offer a huge range of titles (more than 7 million) which really sets them apart from the rest of the crowd.
But is simply offering so many titles enough? I don’t think so. I mean, how difficult is it for someone with deep pockets to simply replicate this? Not very. In fact, the Bansals started their venture with just Rs. 5 lakhs. So what does Flipkart have that makes its model so robust? An amazingly well-oiled warehousing and delivery system. This ensures that deliveries occur within promised times all over India. And with a business volume of nearly 2 lakh books every year, one can imagine how important logistics is to this business.
So what’s my take on Flipkart? I personally didn’t like the website interface so much. And this one’s supposed to be a newer one. It didn’t inspire me at all. And they still haven’t turned a profit yet. But on the positive side, they have the scope and the scale. They are adding new product lines such as movies, music, games, cameras and computers. They are coming up with creative ads and improving operations. They have just received another round of funding. All in all, there’s no doubt that Flipkart has tremendous potential.
Featured Image Source: http://www.flickr.com/photos/nadircruise/5489567292/

What is Big Data?

In the process of discovering and determining these insights, large complex sets of data are generated that then must be managed, analyzed and manipulated by skilled professionals. The compilation of this large collection of data is collectively known as big data.

So, how big is big data?

Most professionals in the industry consider multiple terabytes or petabytes to be the current big data benchmark. Others, however, are hesitant to commit to a specific quantity, as the rapid pace of technological development may render today’s concept of big as tomorrow’s normal. Still others will define big data relative to its context. In other words, big data is a subjective label attached to situations in which human and technical infrastructures are unable to keep pace with a company’s data needs.

The Three – and Sometimes Four – V’s of Big Data

Though the word big implies such, big data isn’t simply defined by volume, it’s about complexity. Many small datasets that are considered big data do not consume much physical space but are particularly complex in nature. At the same time, large datasets that require significant physical space may not be complex enough to be considered big data.
In addition to volume, the big data label also includes data variety and velocity making up the three V’s of big data – volume, variety and velocity. Variety references the different types of structured and unstructured data that organizations can collect, such as transaction-level data, video, and audio, or text and log files. Velocity is an indication of how quickly the data can be made available for analysis.

In addition to the three V’s, some add a fourth to the big data definition. Veracity is an indication of data integrity and the ability for an organization to trust the data and be able to confidently use it to make crucial decisions.

Understanding the Big Picture of Big Data

To gain a better perspective on how much data is being generated and managed by big data systems, consider the following noteworthy facts:

• According to IBM, users create 2.5 quintillion bytes of data every day. In practical terms, this means that 90% of the data in the world today has been created in the last two years alone
• Walmart controls more than 1 million customer transactions every hour, which are then transferred into a database working with over 2.5 petabytes of information
• According to FICO, the credit card fraud system currently in place helps protect over two billion accounts all over the globe
• Facebook currently holds more than 45 billion photos in its user database, a number that is growing daily
• The human genome can now be decoded in less than one week, a feat which originally took ten years to complete

Uses of Big Data

As stated earlier, organizations are increasingly turning to big data to discover new ways to improve decision-making, opportunities, and overall performance.  For example, big data can be harnessed to address the challenges that arise when information that is dispersed across several different systems that are not interconnected by a central system. By aggregating data across systems, big data can help improve decision-making capability. It also can augment data warehouse solutions by serving as a buffer to process new data for inclusion in the data warehouse or to remove infrequently accessed or aged data.
Big data can lead to improvements in overall operations by giving organizations greater visibility into operational issues. Operational insights might depend on machine data, which can include anything from computers to sensors or meters to GPS devices. Big data provides unprecedented insight on customers’ decision-making processes by allowing companies to track and analyze shopping patterns, recommendations, purchasing behavior and other drivers that are known to influence sales.

 Big Data - Videos

Top 10 IT Skills on Demand

1. Puppet

"Open source has changed the technology landscape, and you're seeing that in the skills that proliferate as well as the types of jobs employers are hiring for," says Dice.com's Goli. "The more agile, flexible and scalable a technology is, the more companies can develop proprietary products that help them gain an edge," and open source certainly fits the bill.
Puppet, an open source IT automation tool with the cute name, is anything but child's play. It has gained a foothold with some of tech's biggest players and Puppet Labs completed a $40 million round of investment funding in June. Goli says Dice.com expects tech professionals with automation and orchestration experience to continue to be on hiring managers' wish lists.

2. Cyber security

It's no surprise that two of the top 10 skills on the list (along with No. 9, Information Security) address keeping data secure, Goli says. As an increasing number of data breaches make headlines and consumer anxiety concerning personal information rises to a fever pitch, expect demand for this skill to continue to grow as companies look for tech professionals who can both proactively and re actively attend to security gaps and threats

3. Big Data

Big data is a big deal, whether the industry is marketing, pharmaceuticals, healthcare, defense systems, video games -- the category is important almost everywhere these days, along with subsets of big data skills such as NoSQL (No. 4) and Hadoop (No. 6), says Goli. "Companies crave data that can help them gain insight into customer behavior, strategize for the future and predict future growth opportunities," he says. Tech pros who can extract intelligence from data have a secure, lucrative future, he says.

4. NoSQL

As mobile apps become even more ubiquitous and big data and the cloud gain even greater mainstream acceptance, NoSQL databases are also increasing their popularity in the marketplace, according to Dice.com. Professionals who know when -- and when not to -- use these new approaches will bring much-needed flexibility, efficiency and agility to their companies' operations, Goli says.

5. Salesforce

Two trends are driving demand for Salesforce, Goli says: the sprawl of cloud computing and the resulting increase of Salesforce.com implementations and businesses' need to foster more intimate relationships with customers and analyze the data associated with those relationships. As implementations of the CRM tool increase, companies will require tech professionals who can customize Salesforce.com as well as ensure solutions are scalable, he says.

6. Hadoop

The value of big data is in the capability to analyze and interpret massive amounts of stored information. Hadoop, the open source Apache framework that facilitates this analysis and interpretation, will continue to gain traction in the market, says Goli. Hiring managers use Dice's Open Web to find Hadoop professionals who also have NoSQL (No. 4) and Big Data (No. 3) experience, he adds

7. JIRA

Project and issue-tracking software JIRA has found a foothold in both startups and in big enterprises, especially those with large teams of software developers. Reporting and issue tracking is an obstacle all organizations face, and the demand for technology like JIRA and for professionals who solve problems, track issues and report on project workflows will continue to see explosive growth, says Goli.

  

8. Cloud

Businesses love technology and talent that can save them money and maximize efficiency, which explains the continued growth of cloud tech and the demand for talent with related experience, says Goli. Intuit predicts that 78 percent of U.S. small businesses will have fully adopted the cloud by 2020, as compared to 37 percent today. As cloud computing grows, job opportunities should soar well into the future, he says.

  

9. Information Security

As businesses struggle to keep an increasing amount
of customer and user data secure, information security skills and experienced talent will remain in demand, Goli says. "Threats show no sign of slowing down; neither does the demand for security professionals," he says.

 

10. Python

Python is an oldie but goodie -- it's a mature language that continues to dominate after 25 years -- and is a foundational language taught in college-level programming courses, Goli says. "Today's Python students will be well-armed when they enter the workforce with these skills," he says. "Both large companies and startups alike understand that it's a simple, elegant and powerful language with which to build Web properties."