Data Analytics
In a century where several big companies rule the roost, it often puzzles us as to what makes them reach such great heights. Of course, there is an immense amount of hard work, determination, perseverance, intellect and sufficient business skills involved in this endeavor, but in recent times, another phenomenon has also made into this list. We call it – Data Analytics.
At the introductory level, we can define Data Analytics to be the process of navigating through business data and inferring accurate insights from it. In commercial terms, “Data Analytics is the science of examining raw data with the purpose of drawing conclusions about that information.”
Whether you call it big data, analytics, business intelligence or data analysis – they all refer to the single phenomenon and are in use interchangeably. However, it is important to consider the fact that we can now collect and analyze data in ways that weren't possible even a few years ago. Big Data is starting to transform most areas of business, industry, research and most other parts of our lives.
Big Data does not only refer to the ever-increasing size of data sets we can now analyze, but it also relates to the speed at which it is created and used as well as the different types and structures of data we can now analyze. In many top-notch business organizations dealing with terabytes of data, it is very time-consuming and tedious to evaluate information and analyze what is important and what is not. In such cases, Data Analytics comes to the rescue. With the help of advanced technologies and high-end computing software like high-performance data mining, predictive analytics, text mining, forecasting and optimization on big data enable us to drive continuous innovation and make the best possible decisions. Also, organizations are discovering that the unique properties of machine learning are ideally suited to addressing their fast-paced big data needs in new ways.
Before we dive deeper into this vast ocean of Data Analytics, let us get to know what makes it so important and where does it crop up from in the first place. In 2012, the largest chunk of pupils using Data Analytics hailed from the USA, occupying an aggregate of 32% as a single country. Next in line was Western Europe with occupancy of 19%. China was not far away with an aggregate of 13% and our proud country India managed to enforce its presence on the global map with a net holding of 4%. The rest of the world settled for a cumulative share of 32%.
As per the statistics of 2012, the recorded data across the world exceeded 2.8 Zettabytes (seventh power of 1000 bytes). It is predicted that the total data or storage capacity on our planet will reach 50X of the present value. Now, as you can understand, it is huge, very huge! If we analyze it, we also account for this extraordinary amount of data. Right from uploading a song to updating your status on Facebook – we are doing our bit to increase the global data statistics.
Nearly half of the global data if measured in distance parameters can stretch up to 5000 miles. In other words, just half of the total global data is high enough to spread from Tokyo to New York! However, only 33% of this information is tagged and is useful. Also, sadly, only 0.5% of the global aggregate data is being analyzed; rest of the information is wasted because it is not appropriately monitored.
Interestingly, data that is organized is useful, while the unorganized data is serving no valuable purpose. Data has to be studied, analyzed, processed and converted to put it to some good use. Therefore, with just half of a percent being analyzed, it is evident how much amount of valuable data we’re brutally wasting.
In general data analytics terms, Information is potentially useful concepts based on data. Knowledge is our understanding of this information. Finally, Wisdom is the know-how on how to utilize this knowledge. For example, Ethical Hacking is a form of Wisdom of this data.
Applications:
• Banks and Credit Cards companies use Data analytics to analyze the withdrawal and expenditure patterns of their clients to detect possible cases of theft or fraud.
• E-commerce websites like Amazon, Ebay, Flipkart also use Data Analytics to study website traffic and to determine the demand for various kinds of products across several domains.
• Data Analytics is used in healthcare to find new cures for deadly diseases like Cancer, to detect, optimize and even predict the occurrence of diseases even before the appearance of symptoms
• Police and Anti-criminal bureaus use Big Data or Data Analytics to foil terrorism, predict attacks and mishaps way in advance
• Athlete performances can be gauged and monitored where data from sensors in equipment and wearable devices can be combined with video analytics with the help of Big Data systems that was hitherto, impossible
• Big Data is used to improve our homes, cities and countries (basically, our lifestyle) by e.g. optimizing the heating or lighting in our homes, the traffic flow in our cities, or the energy grid across the country.
Opportunities for Students:
Of course, it all seems exciting and interesting to be part of this Global Revolution of Data Analytics and its allied fields. Nevertheless, before you make a decision, you must take note of a few important factors:
* The rosy picture of earning a prominent position in this field will take at least 3-5 years to materialize. Until then, you’ll have to work hard continuously and prove your mettle to reach the desired status and salary – the no-brainer part
* Many companies believe in hiring fresh graduates for this job profile. Therefore, if you’re a seasoned worker, then you may not fit the bill for them.
* Background change is often looked on with suspicion and skepticism; therefore, if you’ve switched your fields with different job profiles, then you may be in an awkward position; although it isn’t always the case.
* Big Data or Data Analytics is a knowledge-based domain. Therefore, you need to be well equipped with sufficient skills and be updated with the latest information to excel in this field.
How soon will you get a job?
Now, this is inevitably the most important thing for all students; that’s given. Pupils interested in taking up this field must work on the below attributes to be in the best standing:
• Problem-solving skills
• Learning Agility or your speed of picking up necessary Analytical skills
• Analytical thinking
• Communication Skills
• Presentation Skills
If you’re blessed with these qualities then, you are more than likely to get a job within six months of setting out on an Analytical job hunt. If not, you must make sure that you’re polishing your skills now and then until you stumble upon that coveted position of your field.
In some cases, it is possible that it may take anywhere between 6 months -2 years, if that’s the case, then stop and seriously analyze what’s going wrong. You may choose to work harder on your skills too, which is always a good thing.
Additionally, this time-frame is valid for the markets with an acute scarcity of data Analysts. For other geographies, the scenario might be completely different. Therefore, the job prospects are extremely subjective. But having said that, being sufficiently educated in this field with more skills under your belt will certainly land you in a good position. All you need to do is learn to work harder and establish a strong bond with perseverance!
How to increase your chances of getting into the Data Analytics field?
If you’ve decided that you will not die without giving a shot at Analytics, and promise to give your blood and sweat to this area, then you’re in the right place. Below are the links to a few online courses you can take up to better your chances of being a successful Analyst. What’s more – apart from learning these courses from the comfort of your home, most of them charge a nominal fee and provide a certificate of your learning too. Now, that’s a win-win situation; is it not?
• Enroll for a Data Analytics course at Coursera. It goes deep into teaching you the nuances of the subject.
https://www.coursera.org/learn/analytics-excel
https://www.coursera.org/specializations/jhu-data-science/1
• You may also try Lynda for in-depth knowledge and training
http://www.lynda.com/Data-Analysis-training-tutorials/1303-0.html
Further, you may choose to be a part of erudite Linked In groups that can help you to bolster your knowledge and expertise in this area.
https://www.linkedin.com/groups/35222/profile
Furthermore, read good blogs, newspapers, and articles for the same
http://www.kdnuggets.com/
http://www.kaushik.net/avinash/
http://www.smartdatacollective.com/
These all will help you in getting proper insights into this field and help you a lot to be prepared for this highly competitive industry.
Final Word of Advice:
Unless you’re willing to give your heart and soul to numbers, crunching them, zillion bytes of data and all other things encompassed – you may not be able to do complete justice to this field.
It’s no way intended to discourage or demotivate you from following up your passions, but it’s a kind suggestion to expose the reality of Data Analytics career demands.
Therefore, you have what it takes to come out happily, and numbers and data make you euphoric, you’d be very well geared up to become successful as a Data Analyst.
Here’s wishing all the passionate, brave souls a thumbs up and the very best in your future endeavors, our Would-be Data Analysts!