It’s Data Science all the Way ….

(T-60)

Hello Readers,

You’re favourite author Guru along with team ARHAATHS back with another new informative article on the latest technology  that’s heavily in demand in terms of workforce. Also, are you wondering what the T-Minus is all about?? DON’T exhaust yourself… Read along for more information on what rocket is all about from the minute from launch till it escapes the orbit and in its journey!!

This article is a light version of juxtaposing of a 3-Stage Rocket Launch and Data Science (although there’s a lot more that goes into both these which is practically impossible for me to mention in one article as I am an expert in neither fields of discussion)

Alright, (T-30),

Let me start the article with a small example, how does your mom know that you like sweets so much?? She observes your behaviour(patterns) every time a sweet is in front of you.. well this small example gives us insights on you as a person and sweets as a food that you like to savour so much. well imagine the same sort of activity done by the seller of that sweet over a period of time to your parents, I mean to say he will analyse the frequency of them buying the sweet from the shop based on the time, date, day of week etc.., and predict that next week on a Friday your dad will come at 8.0 PM to buy a box of sweets co he’s late again and your mom is furious on him and he has to deliver the sweets to calm her down… well, don’t imagine, that’s the truth of life 😛 hahaha…

It’s all about Data Science!!

(T-20)

Anyhoo… What the seller did was a type of data analysis and pattern recognition, predictive analysis to be precise…

Now let me dial down the intensity and start off slow…

(T-10)

To all the folks who are wondering what’s what in this field of data and to people who think your experts in the field (Help me become one of you, please!!!) I have written this article to simplify many notions and terms.

NOTE: I would like to mention that this is my view and none of them is intended to deviate or distract or misinform you on these topics.

(T-0)

Level 0 Folks… “Wohoooo, We have a launch, Lift OFF Normal ”.

One small step for us, but a giant leap towards data science :P,

T-(-1), (-2), (-3) …… so on …. Until T(-K) + C (I’m laughing hysterically now… Analysis of algorithms effect for those of you wondering what it is that I feel so proud about)

So back to our topic, wondering – What is Data here?

Any information that is of value and can be represented as facts and figures and be used for analysis/ investigation, basically anatomization for the use of the person who is performing it. It can be in raw form i.e. A mixture of valuable & gibberish content (garbage data amidst normal data, Just like my articles, No? Okay).

Alright now the Data Rockets gone live, no counts 😛 Just data…PUN Intended!!!

Level 1 folks, Rocket has exited the atmosphere now, prepare to detach the strap-on’s.

What is Data Science?

An area of science that is designed to learn/study the structure and behaviour of data via various scientific methods, algorithms etc., to gain suggestible perceptions. 

“Confirmation, Rockets Strap-on’s have discarded.”

Command Centre to ALL: “We’re Proceeding towards end of first stage separation.”

We are going to understand now what traditional data, Big data, business intelligence(BI), Data Science(as a part of process) and, the Big Boss of them – Machine Learning/Artificial Intelligence are all about.

Traditional Data & Big data: These as described above are information that are essential for any person working with data, they are a part of your 0th stage analysis.

These data , first need to be cleansed, and then labelled according to its type,

Traditional data involves – categorical data and numerical mostly,

Big Data covers of text, images, sound, video. 

Wherever these data are put in, we need to follow a standard procedure of filling missing values and most importantly (which goes without saying) cleansing the data(removing junk data and irrelevant data according to the scenario that’s in need).

Business Intelligence:

After the traditional/ big data are pre-processed, structured & ready for further process, the progression of analysing this existing data to create forms of tables, charts, reports and other forms of metrics for the users to gain real insights is usually known as BI.

Observe the above, we’ll find out that whatever we’re generating or performing are based on the data on the events that have completed, meaning on doing the above we’ll arrive at answers to why the events have occurred to some accuracy.  Stage 1 is all about the past findings based on data sets available.

Command centre to ALL: “We’ve completed the first stage separation”

I repeat

“We’ve completed the first stage separation”.

One Stage DOWN, 2 More to go….

The Next TWO topics(stages) in discussion are Data Mining, Machine Learning….

Well, let’s not waste anytime beating around the bush.

Automatic Second stage ignition commencing….

Data mining is exploring for unseen, legitimate, and potentially useful patterns in the available data. It is all about discovering unpredicted/ previously unidentified relationships amongst the data.

It is a multi-disciplinary speciality that uses the Big-Boss Machine Learning, whole lot of Statistics, Artificial Intelligence and database technology.

Also Known as Knowledge discovery, Knowledge extraction, data/pattern analysis, information harvesting, etc. according to the person’s comfortability in naming this in the process.

Also, touching on the famous predictive analytics topic, we access potential future scenarios by using statistical methods such as different types of regressions, etc.,

The ABOVE, THESE ARE A DATA ANALYST/SCIENTIST’S CORE JOB…

 Alright Moving on to Stage 3,

Jettison of payload fairing’s, and automatic third stage ignition commencing

A data scientist also utilizes the artificial intelligence tools to predict the behaviour of data in extraordinary ways through supervised learning, unsupervised learning and reinforcement learning.

These used in combination with programmed algorithms are Labelled Machine Learning since the machine is programmed to detect the patterns and at the end maximises the findings with minimal intervention of the programmer.

Finally, and oh finally I would like to give you a brief distinction between Data Analysis and Data Analytics,

For most of you it’s just a synonym, right? No… You’re Wrong…

When it comes to science of animals(Zoology), do you say ornithology and entomology are same ? No!! Right!?! One is the study of insects(entomology) while the other is the study of birds(ornithology).

 Analysis is the action performed on data to find out or reason the past events, to drive decisions in the future you need what the past looked like.

Well Analytics, is the action of applying the statistical models to effect to actually forecast the data that are about to show up(e.g. Weather or GDP or stuff like that), well I am not saying it is a witchcraft or perfect future vision, but it is about predicting the state closest to the actual outcome. The efficiency of any machine learning algorithm is not recorded at a 100% till date.  

So that settles it….

The Satellite has entered the moons atmosphere is about to send us awesome pictures…for more details on the rockets launching activities visit ISRO’s/NASA’s Website please! This was mentioned in the article to not bore you …Verbose Much! Well I really can’t help it… this is a form of writing apparently 😊 thank you for reading it though….Read ON, I am not done with you yet at least not so easily … I like to share whatever I know!!!

Well here are Some of the real time applications of data analysis & BI:

Sentiment analysis in social media, historical success of games played(all types game statistics), incident portal reports, escalation matrix index, price optimization, time optimizations on tasks, inventory management, sales data etc..,

Some real time projects using Data Analytics/ML/AI/Data Mining are:

Sales Forecasting, Market prediction using time series methods, credit card fraud detection, face recognition etc..,

Some Tools used in different phases of a data science project are:

R Studio, Python, Scala, Hadoop, Excel, Microsoft SSIS, IBM SSPS, SAS, Power BI, Tableua, SQL, Qlik, Azure, MATLAB, RapidMiner etc…,    

Some Advice for upcoming young’uns and all Data Science enthusiasts – The sexiest and one of the most high paying jobs of the 21st century, with this statement as background more and more people overflow with the certifications from local establishments and online portals such as Shaw academy, edureka, Udemy etc.., but one who knows all is not essentially important to organizations, but the one who knows the necessary skills and knows them to the deep end where he has struggled with loads of errors on practice and is JUST not boasting off with certifications but also has tons of projects in his armoury to show as experience with many proficient certifications.

Well as my father would say about many things in life, It’s Just Data Science and not Rocket Science.

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