Big Data Career Is The Right Way Forward. Know Why!
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If you’re already from the IT industry, you must be aware that Big Data is the talk of the day. Be it, new startups coming up with innovative business models, or your colleagues moving on to join those startups, for some reason, today’s greener pastures seem to be the Big Data industry.
If you’re wondering why, then I recommend you read this till the very end because this can be a self-exploring blog, leading you to what you’re destined for.
So, why all this HYPE surrounding BIG DATA?
Is it just another domain which is gonna land refugees from all other domains on a temporary basis? Or, will it be here for the long-haul?
If I were to take a guess, I would say that, not only is it going to be here for the long-haul, but the Big Data industry is going to be at the epicenter of technological advancement.
Because everything is about DATA!
Just like the Sun rises from the East and sets in the West, continual use of computing/ non-computing devices will result in an outburst of unmanageable data.
When this data crosses the threshold, of being handled by Excel or any Database Management System, we term it BIG DATA.
Think, which was the last product you purchased from Amazon? Which can be the next product you might purchase based on past activity? Answers to such questions are stored in Big Data.
Is there a growing trend behind a product? Or, is there a declining trend? Will a customer buy ‘Stockings’ when he purchases ‘Shoes’? These are business problem-solving questions.
And, these questions can be easily answered by using Big Data Analytics.
After all, what’s the use of data, when you’re not analyzing it?
So, is Big Data completely about Analytics? Not completely, but Analytics is the Ultimate Prize.
Other major streams in Big Data are Storage and Management.
This is where you as a professional can contribute. You can assume the role of either:
- Big Data Engineer
- Big Data Solution Architect
And make sure that the big data that is generated, is alway available and it can be used for analytics at a later point of time. So this brings us to the question…
Where is Big Data stored?
Can it be stored in an Excel file? Can it be stored in a relational database system?
If it could have been, then it would have been!
And be called something different all together. Maybe something like Excel-Data or RDBMS-Data :D
And that would take us back to STEP1:- Why can’t Big Data be managed using Excel? Because Big Data is just too hot for Excel to handle. And even other database management systems for a matter of fact.
So, what is the alternative?
For handling Big Data, we have HADOOP. You might be aware of this word too. But, you might be wondering, how exactly does it work?
For starters, HADOOP is a product of APACHE Foundation. Apache is an American non-profit organization which supports the development of open-source software.
Hadoop is defined as an open-source Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment.
What can Hadoop do, but Excel can’t?
Process and understand unstructured data! Structured data which is in tabular format or otherwise can be easily dealt with. Excel can do it, and so can any other RDBMS.
But when readability reduces, and data is unstructured, that is where Big Data tools like Hadoop score. An example of unstructured data is syslog. A sample image is below.
Such logs are definitely not queryable using Excel.
Hadoop, like Big Data tools, can understand data as it is, by unearthing patterns and forming relations between various fields. And once the data has a relational touch, it is Analytics-ready.
Analytics is what will make a business impact on an organization! Your career will largely benefit by its involvement in this Big Data domain.
“Can I make it as a Hadoop-er?”
…may be the next question on your mind. And rightly thought, Big Data is a market which is as hot as ever, and as important as ever.
Without Hadoop, companies will have a tough time dealing with Big Data. And without skilled professionals like you, companies will have a tough time dealing with Hadoop.
There is a report that says, there is a talent deficit in this domain.Talend deficit means, less professionals but high demand. And this is on a global scale and not restricted to a particular geography.
Do you want numbers?
A McKinsey Global Institute study states that the US will face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data by 2018.
Career advice to you? Surf when the tides are low!
But are you restricted to only Hadoop?
Not really. There are a number of tools for processing Big Data, and Hadoop is considered as one of the best. But, not every-time!
There are times when Hadoop is not the best-fit. For example, if you are a non-technical person who is not very good at writing MapReduce programs.
In such cases, you can use TALEND, which gives you a graphical user interface to do whatever you would have otherwise done with MapReduce.
For writing simpler Java codes, you can use PIG.
If you want to run SQL-like queries on Big Data, then HIVE can be used.
If you want to use data stored in a NoSQL database, then HBase can be used.
For performing analytics in real-time, you can use SPARK.
These are Big Data tools, which go hand-in-hand with Hadoop, yet they do not replace Hadoop whatsoever. They are Hadoop Add-ons for Big Data.
Besides, there are a couple of more tools like SQOOP, FLUME, OOZIE, etc which can be integrated with the Hadoop framework for solving various business problems.
What does the industry expect from you as a Big Data Expert?
The industry is in dire need of BIG DATA ARCHITECTS who can build an end-to-end big data solution for their organizations. Big Data Architects are those with expertise in all of tools before-mentioned.
Here is a testimony by an Edureka learner on Big Data Hadoop Training course:
Become a BIG DATA ARCHITECT starting from Edureka’s Big Data And Hadoop certification training which helps learners become expert in HDFS, Yarn, MapReduce, Pig, Hive, HBase, Oozie, Flume and Sqoop using real-time use cases on Retail, Social Media, Aviation, Tourism, Finance domain.