Big Data is the amount of data that cannot fit into the memory of a single computer system. With each passing day, Big data is growing bigger, is more difficult to make sense of, is being generated at a much faster rate and this trend is only going to intensify in our data-driven digital world.
- Updated on: 04th Dec, 17
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Today in our digitally-driven world data is one of the prime aspects of any business enterprise. Today’s business enterprises are data-driven and without data no enterprise can have a competitive advantage. Data is the new currency and oil of our generation.
Big Data Definition
Big data has different definitions wherein the amount of data can be considered to be called it as big data or not. Today’s big data might be tomorrow’s small data but it is considered big data when the size of the data itself poses a problem.
“Information is the oil of the 21st century, and analytics is the combustion engine”
– Peter Sondergaard, Senior Vice President, Gartner.
3V’s of Big Data
If you want to understand big data then you have to understand the big data basics. The 3Vs of big data include the volume, velocity, and variety. Most of the big data comes in high volume which is the reason why it is called as big data. The next attribute of big data is the velocity with which the data is coming. In today’s digitally disruptive world the most of the data is coming in a high speeds. This is true with the social media data and this is true with any other data. The third attribute of big data is the variety of big data. Today’s data is not just structured data. Gone are the days when it was possible to work with data using only a relational database table. The data which is coming today is of a huge variety. It could be data in tabular columns, data through the videos, images, log tables and more. These are some of the aspects of big data.
Big Data Concepts
Today’s organizations are data-driven organizations and due to this when the data is converted into nuggets of information then there is a huge value that enterprises can extract out of it. Data is the new currency of our generation. Some of the largest organizations are sitting on a huge amount of data and this data needs to be converted into a format that can be easily understood by the right professionals in the organizations in order to drive the necessary changes to help the company grow and progress.
“The world is one big data problem.”
– Andrew McAfee
There are a lot of big data tools that are extensively used for making sense of the data and converting it into valuable insights.
- Data organization
Organizing the data is a big part of working with the data. This means deploying various techniques on data so as to cleanse it, segregate it and convert it into a format that is easy to understand. There are various tools for working with big data like some tools are good for structured data, some for unstructured data and so on. Then there are other tools for working with the different stages of data extraction, transformation and loading.
- Data visualization
This is the part of the big data process wherein the data is converted into visual insights that can be easily interpreted into a manner that can be easily identified by anybody regardless of their technical and big data skills. There are various tools that convert the data into visualize insights through neatly prepared charts, reports, dashboards and more.
Check this insightful video on Big Data
The types of Big Data
1. Structured data
This is the type of data that is stored in the regular databases in terms of the rows and columns giving it a definite structure. Previously most of the data used to fall under this category but as and when our penchant for watching videos on YouTube, Facebook grew we ventured into a world of unstructured data wherein the regular relational database management systems could no longer sort the data into tabular format. Most of the data that is part of the structured format includes the company employee details, census records, economic data and so on.
2. Unstructured data
This is the type of data that can be put into a regular row and column based format. Today over 80% of the data is unstructured data and due to this there are a huge set of tools that are deployed for making sense of the unstructured data which is part of the Big Data Hadoop ecosystem. Going forward the percentage of unstructured big data will only increase due to the huge amounts of sensor and machine-generated data that we will be seeing as part of the Internet of Things revolution that is underway.
3. Semi-structured data
This is the type of data that straddles between the structured and unstructured data formats. So basically the data which is unstructured might not be so unstructured after all. The unstructured data that can be converted into structured data through the addition of certain keys, attributes or other characteristics through which they can be arranged or sorted in a database. Such kind of data is called as the semi-structured data.
Big Data Companies
Today Big Data is so rampant that one has to look which are the companies that are not deploying Big Data. Starting from technology companies like Google, Apple, Amazon, Microsoft all the way to mining companies like Rio Tinto, retailers like Walmart and hospitality companies like Airbnb are all using big data and big data analytics.
Here we will be talking about a few of the companies that are using Big Data at scale :
- Amazon – Getting insights on all the customer data and providing better user experience
- Google – making sense of what the customer is searching for and providing better search results
- Rio Tinto – finding out which are the mining rich places and how to go about getting the best output
- Walmart – providing customers what they are looking for in terms of products, discounts, etc.
Big Data Projects
Since Big Data is a big part of every organization we are here concentrating on some of the most important big data projects that can help you understand the type of ways in which you can work using Big Data in the real world.
MovieLens Dataset Project :
This is a big data project that involves working with the MovieLens data that is available in the form of rating data sets. Some of the aspects of this project include:
- Writing a MapReduce program for finding the top 10 movies by working on the data file
- Use Apache Pig to create the top 10 movies list by loading the data
- Deploying Hive for creating the top 10 movies list by loading the data
Hadoop YARN Project :
This project involves working with the Hadoop YARN which is part of the Hadoop 2.0 ecosystem thus letting it decouple from the MapReduce application for computing of big data. This includes working on the Hadoop central resource manager. Some of the aspects of this project include:
- Movie data importing
- Appending the data and using Sqoop to bring data to HDFS
- Determining end to end transaction flow.
Hive Table Partitioning Project :
This project involves working with Hive data table for partitioning of data. With the right partitioning the data can be read, deployed on HDFS, can be made to run the MapReduce jobs faster. There are different ways of partitioning of data through Apache Hive. Some of them are as below:
- Dynamic partitioning
- Manual partitioning
Connecting Hadoop with Pentaho ETL project :
This project involves working with Pentaho ETL tool and connecting it with Hadoop. Some of the aspects of connecting Pentaho with Hadoop are as follows which you will be working in this project:
- Deploying the graphical build for reading and writing of data into Hadoop
- Data orchestration, data movement and other aspects of working with data
- Working with pixel perfect data reporting
- Interactive data analysis with Pentaho data analyzer.
Big Data Problems
Here we discuss some of the problems associated with big data. Since there is so much of big data sometimes it is hard to find out what the real valuable data is and what the noise in it is. The second issue is with regard to data that is in silos. Since data is coming in from various sources most of the data is not compatible with each other and there is no uniformity and hence this issue needs to be taken care of. Sometimes there is too much inaccurate data and all this should be taken into consideration before deploying it for applications in the real world.
Big Data Trends
This section includes working with Big Data to find out the different ways in which the world of big data is moving simultaneously in different directions. One prominent way in which big data is moving is towards a future where open source is a big part of the big data world. The next big data trend is towards the tools which support in-memory processing like the Apache Spark tool which is used in real-time analytics. Machine learning and predictive analytics are some of the other aspects in which there is a lot of action taking place in the big data domain.
Study the Machine Learning Course to know more about Predictive Analysis.
What can you do with Big Data?
Business organizations are very much dependent on big data systems for deriving valuable insights. It helps to optimize business operations, streamline the entire lifecycle of the business from raw material to the end product. Big Data systems provide answers faster for business to take the right data-driven decisions. It improves the quality of services and helps to understand the mindset of the customer. It tailor-makes the products and services according to the needs of the customer.
“Data really powers everything that we do.”
– Jeff Weiner, Chief Executive of LinkedIn
The importance of Big Data in today’s world cannot be underestimated as there is a sort of arm’s race between the various organizations in order to get the most insights into the mindset of the customers and get ahead of the competition.
Working with Big Data
Some of the biggest industries in today’s world are deploying big data at scale in order to get the results that they could only image even just a decade ago. When it comes to working with big data there are certain industrial sectors that are better than others when it comes to implementation of data.
Some of the top industries deploying big data include
- Banking and finance
This is the one of the top domains when it comes to deployment of big data applications. Since banking and finance works exclusively with large amounts of data there is need to make sense of all that data at scale. It could be about understanding the credit risk of a certain customer, analyzing the fraud transactions within millions of genuine transactions, customizing the financial products to millions of customers based on their needs, financial capacity, credit risk and so on.
This is another domain that is exclusively deploying the big data applications at scale in order to unravel the mysteries of the human medical condition, the right mode of treatment depending on the patient medical history and other conditions. Mapping the human genome is a big application of big data wherein the DNA is sequenced in order to understand completely about the human body from a medical point of view.
The domain of education is slowly but surely using big data analytics in order to improve the centuries old education system. It is all about ascertaining the learning capability of each individual in order to tailor-make a certain educational regimen to each student. It is about improving the mode of training so that the students are in a better position to make progress and ultimately become industry-ready by equipping the right skills.
- Media and entertainment
Media and entertainment is going through a sea change thanks to the rapid digitization, influence of social media and such other monumental changes happening in this domain. Big data is playing a big role in this domain to understand the customer sentiment, leverage the power of social media and mobile platforms to deliver the right content at the right time to the right audience. It is also extensively used in content customization, recommendation and measurement for giving a holistic experience to the end-user.
How UPS utilizes Big Data in its proprietary technology ORION?
UPS is the world’s premier courier service agency and the amount of data that is generated at UPS is nothing like anything. Due to this they need a strong data analytics system in order to make sense of all the data at their disposal. This is where the proprietary technology comes into the picture which is nothing but On Road Integration Optimization and Navigation or ORION system for the uninitiated, built by UPS exclusively for its drivers.
This system maps the routes of each driver in the grid and details the entire route that the truck has to take that can help to save precious miles and time. All this leads to huge amounts of savings to the UPS Company that ranges in the millions of dollars each month.
Benefits of Big Data
Some of the biggest advantages of big data include the following :
- Proactively engaging with the customer
You will have your finger on the pulse of the customer. Today there are so many avenues in the customer journey that during every phase the customer leaves a digital trail and the digitally aggressive companies will get their hands on this digital trail and get the insights out of it. All this helps to server the customer better and in a more streamlined manner.
- Generation of new revenue streams
Gone are the days when any company used to stick to its industry vertical. Today there are no more vertical thanks to the power of digitization. If a company is an ecommerce player then there is nothing that can stop it from going into cloud computing and storage. The example of Amazon is a prime example in this arena.
“Data is the new science. Big Data holds the answers.”
– Pat Gelsinger, CEO of VMware.
- Product and service redesign to meet customer needs
A lot times it happens that the initial product created by a company might be of inferior quality or just not up to the expectations of the company. But this need not deter the forward-thinking companies. There are enough insights that the customer is giving to help a company tailor-make its products and services as per the needs of the customer. All that a company needs to do is dig in deeper into big data and get all the insights that are needed for creating a world-class product or service.
- Performing risk and competitor analysis
Every business comes with its own set of risks and also there is the risk of competitors trying to dwarf a company and eventual put it out of business. But thanks to big data today it is an even playing field. It is unlike the good old days when the game was biased in favour of the big players. But big data is making it a very democratic way of running the business. Get enough data, deploy enough tools to make sense of it and you are at the top of your game in no time.
- Data safekeeping and regulatory compliance
Today due to the deluge of big data there are a lot of regulatory compliance that needs to be adhered to either through government regulations or through other industry related regulatory authorities. So big data also helps the organizations to keep the data safe and keep it in accordance with the regulatory compliance. If there is a breach or failure to keep up with the rules then it can be easily flagged and necessary changes can be brought about without any hassles or delay.
- Streamlining business processes and maintenance
No business can stay immune to the winds of change that is sweeping the corporate world thanks to some powerful forces brewing in from all directions. Today changing of the domain or tapping into an international market is just a matter of intent rather than a big structural change. All this is possible thanks to the power of big data. It is possible to streamline the business processes and tap into an opportunity which even a decade ago was unthinkable. Maintaining a business to keep it in sync with the changing times is also easier thanks to the deployment of big data and its utilization.
How to learn big data?
Learning big data today is easy thanks to the proliferation of online big data professional training institutes. But not all training is created equal. You need to enroll yourself for the big data training institute which offers hands-on training, is in line with clearing the industry certification like the Cloudera Hadoop certification, and offers you the most updated Hadoop training so you can get the right job after completion of the training. Intellipaat offers the right training to learn big data from scratch which is very important to professionals who do not have a background in Big Data, Hadoop and Data Analytics.
Check the Intellipaat Big Data Hadoop training that is in line with clearing the Cloudera Hadoop certification.
Today Big Data has pervaded every industry that we can think about. Due to this there is a huge change in the way we conduct business. Today customers have grown super-demanding and big data revolution has only fueled their penchant for better products and services. Big data analytics is a whole domain in itself where valuable insights are derived from big data using the various real-time analytical tools. This is only the beginning of the big data flood that we are seeing and things can only get better with time.