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How Data Science Is Getting Better, Day by Day?

Posted on July 7, 2018May 23, 2020 by Dexlab

HOW DATA SCIENCE IS GETTING BETTER, DAY BY DAY?

In the latest Star Wars movie, the character of Rose Tico – a humble maintenance techie with a talent for tinkering is relatable; her role expands and responsibilities increase as the movie gets going, just like our data scientists. A chance encounter with Finn puts her into the frontlines of action, and by the end of the movie, she’s flying ski-speeders in the new galactic civil war, one of the most critical battles in the movie – with time, her role becomes more complex and demanding, but she never quivers and embraces the challenges to get the job done.

A lot many data scientists draw similarities with Rose’s character. In the last 5 years, the job role and responsibility of data analysts has undergone an unrecognizable change – as data proliferation is increasing in capacity and complexity, the responsibility is found shifting base from dedicated consultants to cross-functional, highly-skilled data teams, proficient enough in integrating skills together. Today’s data consultants need to complete tasks collaboratively to formulate trailblazing analysis that let businesses predict future success and growth pattern, effectively.

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Quite conventionally, the intense role of prediction falls on the sophisticated crop of data scientists, while business analysts are more oriented towards measuring churn. On the other hand, intricate tasks, like model construction or natural language processing are performed by an elite team of data professionals, armed with strong engineering expertise.

Said differently, the emergence of data manipulation languages, such as R and Python is surging – owing to their extensive usage and adaptability, businesses are biased towards implementing these languages for advanced analysis. Drawing inspiration from Rose’s character, each data scientist should adapt to newer technology and expectations, and enhance expertise and skills that’s needed for the new role.

However, acing the cutting edge programming languages and tools isn’t enough for the challenge – today, data teams need to visualize their results, like never before. The insights churned out of advanced machine learning are curated for consumption by business pioneers and operation teams. Thus, the results have to be crisp, clear and creatively presented. As a result, predictive tools are being combined with effective capability of Python and R with which analysts and stakeholders are quite familiar.

The whole big data industry is changing, and the demand for skilled big data analysts is sky-rocketing. In this tide of change, if you are not relying on advanced data analysis tools and predictive analytics, you are going to lag behind. Companies that analyze data, boost decision-making, and observe social media trends – changing with time – will have immense advantages over companies that don’t pay attention to these crucial parameters.

No second thoughts, it’s an interesting time for data aspirants to make significant impacts in the whole data community and trigger fabulous business results. For professional training or to acquire new skills – drop by DexLab Analytics – their data Science Courses in Noida are outstanding.

The blog has been sourced from – dataconomy.com/2018/02/whole-new-world-data-teams

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What Makes Artificial Intelligence So Incredibly Powerful?

Posted on October 14, 2016March 15, 2019 by Dexlab

Do you also feel that Artificial Intelligence (AI) is getting eerily powerful day-by-day? That is because the structures of Artificial Intelligence exploit the very fundamental laws of physics and of the universe as per latest research.

These new findings help to answer a long-awaited mystery about a category of AI that employs an interesting strategy called deep learning. These are programs based on deep neural networks hence, the name deep learning. The way this works is that they have multi-layered algorithms in which the lower-level calculations feed into the higher level ones within the hierarchy. These deep neural networks often perform surprisingly well when it comes to solving problems which are highly complex, like beating the world’s best player of a strategic board game called Go or categorising cat photos, however no one truly knows why… Continue reading “What Makes Artificial Intelligence So Incredibly Powerful?”

Prepare For Your Data Science Job Interview With Answers to These Puzzles

Posted on August 17, 2016May 23, 2020 by Dexlab

You may have passed your data science certification course with flying colours, but getting your first break in an analytical job role can be quite difficult. Did you know that more than 30 percent of top tier analytical firms evaluate and select their candidates on their ability to solving puzzles? After all this is the best way to determine that they are logical, with ample creative thinking abilities and are definitely pros at dealing with numbers (a skill must have for data personnel).

The companies are keen on hiring people who have the ability to bring a unique perspective in solving business problems. Such individuals are capable of to offer their hiring firms with a huge advantage over other candidates. But to garner such capabilities an individual must practice regularly with consistent efforts.

As fellow data analysts, we recommend that you develop a daily habit of solving puzzles. They are mental exercises which on disciplined training will help you to get better with time. When employed in a job role that involves having to deal with complex problems everyday such a skill will prove to be an asset.

Are you ready to work out your grey matter cells? Here are the most common puzzles asked at interviews for data science positions:

These questions have been asked to candidates at companies like Amazon, Google, Goldman Sachs, and JP Morgan etc.

Note: Try solving these problems on your own before checking the solution, and feel free to share your logic behind the solutions in the comments below. We are all ears eyes to see how unique someone’s mind can be!

Puzzle #1:

Blind game challenge:

You have been placed in a dark room, there is a table kept in the room. The table has 50 coins atop its surface, out of these 50 coins 10 coins have their tails side up and 40 coins have their heads side up. Your task is to divide this set of 50 coins into 2 groups (not necessarily of equal size) so that both the groups have equal numbers of coins with the tails side up.

Solution #1:

The coins should be divided into two groups one with 40 coins and one with 10 coins, then flip all the coins in the group with 10 coins.

Puzzle #2:

Bag of coins problem:

You have been given 10 bags full of coins; each bag comes with an infinite number of coins. But there is a twist, one of the bags is full of forged coins but sadly you do not remember which one it is. But you do know that the weight of the real coins are 1 gram and those which are forged are 1.1 gram. Your task is to identify the bags in minimum readings with a digital weighing machine that has been provided with you.

Solutions #2:

You need to take 1 coin from the first bag, 2 coins from the second bag, and 3 coins from the third bag and so on and so forth. Eventually you will end up with 55 coins in total (1+2+3+4+…10). The next step is to weigh all the 55 coins together. You can identify which bag has the forged coins based on the final reading of the weighing machine. For instance, if the reading ends with 0.4 then it is the fourth bag with forged coins. And if it comes 0.7 then it is the 7^th bag with the forgeries.

Puzzle #3:

The Sand timer trouble:

You have two hourglasses or sand timers one of which can show 4 minutes and the next one can show 7 minutes respectively. Your job is to use both the sand times (either one at a time or simultaneously or in any other combination) and measure a time of 9 minutes.

Solution #3:

Step 1: start the 7 minute sand timer along with the 4 minute sand timer

Step 2: when the 4 minute sand timer ends turn it upside down instantaneously

Step 3: when the 7 minute sand time ends also turn it down at that instant

Step 4: when the 4 minute sand timer ends turn the 7 minute sand timer upside down and it will have 1 minute worth of sand in it

Thus, effectively 8 + 1 = 9

In closing thoughts:

Hope these questions were enough to get your brain rolling, while a lot of these questions may seem challenging to most of the people, but with a little out-of-the-box analytical thinking you will soon discover that they are not too difficult to solve.

If these questions were simple enough for you, we have plenty more with increasing difficulty. And if all these brain picking has left you overwhelmed to the peak and all you want is to solve real-world data problems, then follow our regular social media uploads advertising latest job openings in the field of data science.

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How Data Science Is Getting Better, Day by Day?

Interested in a career in Data Analyst?