What is Data Science?
In 1962, John Tukey portrayed a field he called “data analysis”, which looks like current data science. In 1985, C. F. Jeff Wu utilized the term “data science” for the first time as an alternative name for statistics.
Data science merges multiple fields, comprising statistics, scientific methods, artificial intelligence (AI), and data analysis, to pull out value from data. The people who practice data science are called data scientists, and they combine a scope of abilities to analyze data collected from the web, smartphones, customers, sensors, and other sources to extract actionable insights.
Data science keeps on developing as quite possibly the most encouraging and in-demand career paths for skilled professionals. Today, successful data professionals understand that they should propel past the traditional skills of analyzing big amounts of data, data mining, and programming skills.
To reveal valuable insight for their associations, data scientists should dominate the full range of the data science life cycle and possess a level of flexibility and understanding to amplify returns at each phase of the process.
What is the use of Data Science?
Here is top 6 use cases of Data science –
- Facebook – Utilizing Data to Revolutionize Social Networking & Advertising –
Facebook is a virtual entertainment head of this present reality. With a great many clients all over the world, Facebook uses a huge scope of quantitative exploration through data science to acquire experiences about the social cooperation of individuals.
However, more than being a social media stage, Facebook is a greater amount of an ad partnership. It involves profound learning for targeted advertising. By utilizing this, it decides what sort of advertisements the users should view.
It utilizes the insights acquired from the data to set users based on their taste and offers them with the advertisements that charm them.
- Amazon – Changing E-trade with Data Science – Amazon intensely depends on predictive analytics to enhance customer satisfaction. It does such through a personalized recommendation system.
This suggestion system is a mixture type that likewise includes collaborative filtering which is comprehensive in nature. Amazon examines the past purchases of the user to suggest more products.
This additionally gets through the ideas that are drawn from different clients who utilize comparable items or give comparative appraisals.
Amazon has an expectant transportation model that involves huge data for foreseeing the items that are probably going to be bought by its clients. It examines the pattern of your buys and sends items to your nearest warehouse which you might use in the future.
Amazon also optimizes the costs on its sites by remembering different boundaries like the user activity, order history, prices offered by the competitors, product availability, etc.
- Uber – Utilizing Data to Make Rides Better – Uber is a famous cell phone application that permits you to book a taxi. Uber utilizes Big Data. All things considered, Uber needs to keep a huge information base of drivers, clients, and a few different records.
It is thusly, established in Big Data and utilizes it to determine experiences and offer the best types of assistance to its clients. Uber imparts the large information rule to publicly supporting. That is, enlisted drivers in the space can help anybody who needs to head off to some place.
As mentioned above, Uber contains an information base of drivers. In this manner, at whatever point you hail for a cab, Uber matches your profile with the most reasonable driver. What separates Uber from other taxi organizations is that Uber charges you in light of the time it takes to cover the distance and not simply the distance.
It computes the time taken through different algorithms that also make use of data related to traffic density and weather conditions.
Even, Uber utilizes information science to compute its surge pricing.
- Bank of America – Using Data to Leverage Customer Experience – 10 years ago, Bank of America was one of the first financial companies to provide mobile banking to its customers. Recently, BoA launched Erica which is their first virtual financial assistant. It is considered as the world’s finest innovation in finance domain.
As of now, Erica is helping as a customer consultant to more than 45 million users all over the world. Erica likewise utilizes Speech Recognition to take client inputs, which is a technological advancement in the field of Data Science.
Moreover, a few different banks like BoA are utilizing Data Science and predictive analytics. Utilizing data science, banking industries could detect cheating in payments and customer details. It additionally forestalls cheats with respect to protections, Visas, and bookkeeping.
In order to reduce the losses, a bank needs to identify fraud quickly. To do this, banks employ data scientists to utilize their quantitative knowledge where they can apply algorithms like association, clustering, prediction, and classification.
Risk modeling is one more significant region that is managed by the banks to control financial activities. Utilizing Machine Learning, banks can limit risk modeling.
Through analytical solutions, banks can make data-driven decisions that are based on transparency and risk examinations. Even, Bank of America identified the high-risk accounts utilizing this technology of big data.
- Airbnb – Using Data to Make Stays More Comfortable – Airbnb is a worldwide friendliness organization that permits you to have facilities as well as find them through its mobile application and site.. It is a data-centric industry. It contains a huge big data of client and host information, homestays and lodge records, as well as site traffic.
Data Science plays a critical role in this organization. It utilizes data to give better search results to its customers. It utilizes segment analytics to examine bounce rates from their sites.
In 2014, Airbnb figured out that users from specific countries would tap the local link, browse the page and photographs and not make any reservations.
To alleviate this issue, Airbnb released a different kinds of version for the users from those countries and replaced local links with the top travel destinations. This saw a 10% improvement in the lift rate for those clients.
- Spotify – Revolutionizing Music Streaming –
It is an internet based music streaming giant that utilizes Data Science for giving personalized music suggestions. Having over 100 million users, Spotify deals with a huge amount of big data.
It utilizes the 600 GBs of daily data produced by the users to create its algorithms to support user experience. Spotify is a data-driven company that uses big data to give personalized playlists to its users.
Spotify has also brought so many analytical features for its artists from the introduction of Spotify for Artists application. This permits the artists and managers to examine their streams, fan approval and the hits they are producing from different Spotify’s playlists.
In the year 2017, Spotify utilized data science to acquire experiences about which colleges had the most noteworthy level of party playlists and which ones invested the most energy in it. It distributes its discoveries on its page “Spotify Insights” to give data about the continuous patterns in the music. Also, around the same time, Spotify bought Niland, which is an API-based item that utilizations machine learning to give better quests and suggestions to its clients.
Compare Data Science Vs data analytics Certification
| Data science | Data analytics |
| Creation of predictive models and algorithms | Draws results from divergent sources of data |
| Wider and more diverse field of activity | Field of activity restricted to the business sector |
| Master in statistics and mathematics | Familiarized with data warehouse, ETL tools and business intelligence |
| Experience with SQL | Powerful command of Python and R |
| talented in Python, R, SAS and Scala | Master in data wrangling |
| Advanced knowledge of machine learning | Talented in data perception |
| Tends to work with unstructured data | Business knowledge and decision-making abilities |
| Apps in sectors like, artificial intelligence, health, blockchain, or website search engines | Application in sectors such as retail, travel, healthcare or marketing |
List of Data Science Certification
- SAS Certified Data Scientist
- Microsoft Certified Azure Data Scientist Associate Certification
- IBM Data Science Professional Certification
- Dell EMC Data Science Certification
- DevOpsSchool certified Master in Data Science
Data Science Certification Path
- Microsoft Certified: Azure Data Scientist Associate ( Exam DP-100: Designing and Implementing a Data Science Solution on Azure)
- DevOpsSchool: Master in Data Science
- IBM Data Science Professional Certification
Data Science Certification Cost
- Microsoft Certified: Azure Data Scientist Associate – $165 USD*
- DevOpsSchool: Master in Data Science – Rs 49,999
- Dell EMC Data Science Certification – $230 (USD)
Best salary for Data Science Certified Professional
The average salary of a data scientist is Rs 698,412 per annum.
Best Data Science Certification Tutorials
https://srdas.github.io/Papers/DSA_Book.pdf
https://people.smp.uq.edu.au/DirkKroese/DSML/DSML.pdf
Best Data Science Certification Video Tutorials
Best Data Scienceg certification excercise dumps
https://www.analyticsexam.com/dell-emc-certification/dea-7tt2-dell-emc-data-science-and-big-data-analytics
Best Data Science certification Ebooks
https://www.packtpub.com/in/data/data-science
- DevOps Certified Professionals (DCP)
- Site Reliability Engineering Certified Professionals (SRECP)
- Master in DevOps Engineering (MDE)
- DevSecOps Certified Professionals (DSOCP)
URL - https://www.devopsschool.com/certification/
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