Data Scientists help find insights about the market and help make products better. They are responsible for analyzing and handling a massive amount of structured and unstructured data and require various tools to do so. Some of the tools used by Data Scientists to carry out their data operations are mentioned below.
Designed for statistical operations, SAS is an open source proprietary software that is used to…
Added by Simran Agarwal on November 25, 2019 at 3:30am — No Comments
Hadoop is an open-source framework that stores and process big data in a distributed environment using simple programming models. It is designed to scale up from single servers to thousands of machines, while each offers local computation and storage. Hadoop divides a file into blocks and stores across a cluster of machines. It achieves fault tolerance by replicating the blocks on a cluster.
Hadoop can be used as a flexible and easy way for the distributed processing of large…Continue
Added by Yoey Thamas on November 20, 2019 at 1:00am — No Comments
We are living in a time of slow yet steady insurgence of data science and AI in our lives. It spans more industries than we’d expect.
Over the past decade, Data Science has stretched out into almost every industry. Form industries like Automobiles and Healthcare to Finance as well as the Gaming Sector. It plays a significant part in the government sectors. So here are some instances of the most impactful…Continue
Added by Sudhanshu Ahuja on August 19, 2019 at 3:00am — No Comments
Data Science is now becoming a highly famous and prestigious field and has also been termed as the "Sexiest job" of the 21st century said in the Harvard Business Review.
The number of data scientist jobs has grown manifolds in the past few years. According to data, the data science jobs crossed over 2 million and is continuing to increase rapidly in…Continue
Ever wondered how most of the fastest-growing jobs in the tech sector today were not even existing a few years ago. It is surveyed that the employees are worried about the skill gap, which is restricting them from shifting to companies which offer better skill development initiative.…Continue
Added by Dave Jarvis on July 31, 2019 at 8:56pm — No Comments
If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…Continue
Added by Ann Rajaram on July 11, 2019 at 2:52pm — No Comments
Summary: The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower skilled data scientists. Salary increases show us whether demand is increasing, and finally we take a shot at determining which skills are most in demand.
Added by William Vorhies on July 1, 2019 at 8:00am — No Comments
Value of adopting Data Science Skills
Data Science is responsible to provide meaning to the large amounts of complex data called big data. It involves different fields of work in statistics and computation to interpret data for decision-making.
Advances in the internet and social media is increasing access to big data. Extraction of meaningful information requires the use of AI and ML by data science. Big data is used in every…Continue
Added by Yoey Thamas on June 4, 2019 at 2:33am — No Comments
In the late 1990s, AI rose to prominence. In 1997, IBM's Deep Blue…Continue
With the introduction of big data, the need for its storage increased gradually. Companies were focussing on building solutions and frameworks to store as much data as possible. When this problem is addressed by big names such as Hadoop, companies shifted their focus on data processing. Here, the popular term that everyone might have heard once is “data science.” Undoubtedly, data science is considered as the future of AI…Continue
Added by Ritesh Patil on December 6, 2018 at 2:00am — No Comments
Summary: Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.
Added by William Vorhies on September 18, 2018 at 9:07am — No Comments
After spending numerous evenings and weekends learning and coding for more than a year, you finally did it! You’ve now completed your data science program, earned your shiny certificate...now what? Chances are you were looking to get a job in data when you signed up for the course. So let’s face this, it is time to get a job! The only thing that’s standing…Continue
The following advice is built from my experience working as a data scientist on a variety of projects across different data & engineering teams. Many data scientists (myself included) do not come from a computer science or software development background, so may not have formal training or good habits in code writing. These tips should help data scientists work collaboratively to write good code and build models in a way that will be easier to…Continue
Added by Jason Byrne on March 2, 2018 at 3:00am — No Comments
You’ve perfected your CV, got great experience under your belt, maybe a PhD and can wrangle data amongst the finest but just how prepared are you for your next interview?
Just the thought of the face-to-face interview stage is enough to strike fear into the bravest of us. Here are a few things to keep in mind and stave off the sweaty palm syndrome. (Bonus tip – if you are prone to perspire through the palm, remember to use a…Continue
Added by Matt Reaney on December 6, 2017 at 2:00am — No Comments
The advancement of new technologies and the development of big data require professionals with skills in many fields: computer science, mathematics, statistics and business.
Every day in the world 2.5 trillion bytes of information are generated, so much so that 90% of the data worldwide have been created only in the last 2 years . This information comes from all sides, sensors that gather climate information, publications on social networks, digital…Continue
Added by Masud Rana on May 4, 2017 at 11:00am — No Comments
According to IBM, the world generates 2.5 quintillion bytes of data every day. A decent chunk of those quintillion bytes is made up of people asking the experts how to break into and excel in the dynamic, lucrative field of data science. An even larger chunk of those bytes consists of convoluted, contradicting answers to that question.
This is, on one hand, a great thing. Multiple prominent data science innovators are out there giving you free advice on your most pressing questions,…Continue
The rise of the data scientists continues and the social media is filled with success stories – but what about those who fail? There are no cover articles praising the fails of the many data scientists that don’t live up to the hype and don’t meet the needs of their stakeholders.
The job of the data scientist is solving problems. And some data scientists can’t solve them. They either don’t know how to, or are obsessed about the technology part of the craft and forget what the job is…Continue
“What if we add these variables?..” is a deadly type of a question that can ruin your analytic project. Now, while curiosity is the best friend of a data scientist, there’s a curse that comes with it – some call it analysis paralysis, others – just over-analysis, but I call these situations “analytic rabbit holes”. As you start any data science project – be it an in-depth statistical research, machine learning model, or a simple business analysis – there…Continue
Added by Karolis Urbonas on March 28, 2017 at 2:30am — No Comments
A data scientist is an umbrella term that describes people whose main responsibility is leveraging data to help other people (or machines) making more informed decisions. The spectrum of data scientist roles is so broad that I will keep this discussion for my next post. What I really want to focus is on what are the distinctive characteristics of a great data scientist.
Over the years that I have worked with data and analytics I have found that this has almost nothing to do with…Continue
Added by Karolis Urbonas on March 20, 2017 at 12:00am — No Comments
We have all read the punchlines – data scientist is the sexiest job, there’s not enough of them and the salaries are very high. The role has been sold so well that the number of data science courses and college programs are growing like crazy. After my previous blog post I have received questions from people asking how to become a data scientist – which courses are the best, what steps to take, what is the fastest way to land a data science job?
I tried to really think it…Continue