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Top Data Analyst Skills in 2021

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According to a report from the International Data Corporation (IDC), the global big data and business analytics market has been expanding at a fast clip over the last several years, leaping from US$122 billion in global revenue in 2015 to US$189 billion in 2019 and driving towards a projected US$274 billion for 2022.

As industries store and assess a huge amount of data online, they need professionals who can take care of managing, organizing, and assessing the information. Many companies are hiring data analysts to meet their data needs. Data analysts need certain skills to excel in their positions.

For a rewarding career as a data analyst, it is essential to master the skills. These skills can also be learned by enrolling in a data science certification. Following are the important technical and non-technical skills which will help an individual to get hired in 2021:

Key technical skills data analyst require

An individual can master following technical skills by doing a big data certification:

• Programming languages

> Python – This is a high-level, general-purpose programming language, which is mainly used in data science, it also offers a remarkable number of specialized libraries. A few libraries of Python are listed below:

a) Numpy

b) Pandas

c) Scikit Learn

d) Matplotlib

>R – This is among the highly used programming languages in data analytics. Its structure and syntax are developed to take care of the analytical tasks. It is one of the most appealing programming languages for businesses as it possesses the capacity to manage huge and complex quantities of data. It consists of packages that ensure to manage the analysis more easily. A few of the packages are listed below:

a) Ggplot2

b) Dplyr

>MATLAB – It is a programming language and multi-paradigm numerical computing environment that offers quick data cleaning, organization, visualization, matrix manipulations, algorithm implementation, and data plotting. It can also execute any machine learning models created in its environment across multiple platforms.

>SQL and NoSQL – SQL or Structured Query Language is used for querying and handling huge sets of data and processing information in relational databases. The unstructured data is stored in a NoSQL database in the format of the document. The NoSQL database querying requires a proprietary language that varies from SQL.

• Data visualization

Data visualization is the representation of the data in an easy-to-digest manner, which includes charts, images, maps, and graphs. It offers better insights into data-driven details. The data analysts also facilitate the business’s decision-makers to identify patterns and understand complex ideas at a glance.

• Data warehousing

In this process, the creation of virtual storage and organization systems of an enterprise takes place. The role of a data analyst is to connect the databases from multiple sources to develop a data warehouse by using the querying languages to manage, monitor, and safeguard the data.

• Data mining, cleaning, and munging

A data analyst gathers information from one or more sources and prepares the data so it is helpful for numerical and categorical analysis. If the data is not stored properly in the database, the data analysts use certain tools to clean the unstructured data and process it through programming. In the munging process, the data is identified, extracted, and integrated to get a dataset, which is helpful for exploration and analysis.

• Machine learning

Machine learning offers computers to automatically learn and perform without the requirement of explicit programming. There are many firms that use highly technical machines to process works. The data analysts should have knowledge on how to build, apply, and train the most appropriate models and algorithms to get solutions for certain problems.

Key non-technical skills data analyst require

Apart from technical skills, there are other non-technical skills that are important for data analysts to be successful. An individual could be a stellar data analyst by doing a big data certification, which assures to provide the soft skills.

• Communication

Communication is a key skill for data analysts. They are needed to explain their findings to various stakeholders, other data analysts, and IT representatives.

• Problem-solving

While performing their tasks, data analysts encounter many technical issues. They are required to effectively problem-solve and come up with better solutions.

• Teamwork

Data analysts should be able to perform tasks with various teams so that they can collaboratively achieve the business objectives.

• Domain knowledge

Domain knowledge is an understanding that is relevant to the particular organization that one works for. This domain knowledge allows resourceful insights into the data and gives data analysts useful information.

Conclusion

By putting an effort and time into a data science certification to learn the aforementioned skills can set up an individual for a successful career as a data analyst.

If an individual wants to get hired in 2021 by a top firm then he/she must enhance their skills accordingly. Always list only those skills on your resume, which you can answer well in the process of the interview.

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Big Data

If you did not already know

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SGAN google


The Generative Adversarial Networks (GANs) have demonstrated impressive performance for data synthesis, and are now used in a wide range of computer vision tasks. In spite of this success, they gained a reputation for being difficult to train, what results in a time-consuming and human-involved development process to use them. We consider an alternative training process, named SGAN, in which several adversarial ‘local’ pairs of networks are trained independently so that a ‘global’ supervising pair of networks can be trained against them. The goal is to train the global pair with the corresponding ensemble opponent for improved performances in terms of mode coverage. This approach aims at increasing the chances that learning will not stop for the global pair, preventing both to be trapped in an unsatisfactory local minimum, or to face oscillations often observed in practice. To guarantee the latter, the global pair never affects the local ones. The rules of SGAN training are thus as follows: the global generator and discriminator are trained using the local discriminators and generators, respectively, whereas the local networks are trained with their fixed local opponent. Experimental results on both toy and real-world problems demonstrate that this approach outperforms standard training in terms of better mitigating mode collapse, stability while converging and that it surprisingly, increases the convergence speed as well. …

Expert-Augmented Machine Learning (EAML) google


Machine Learning is proving invaluable across disciplines. However, its successis often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability ona different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications. …

Multiple Independent Subspace Clustering (MISC) google


Multiple clustering aims at discovering diverse ways of organizing data into clusters. Despite the progress made, it’s still a challenge for users to analyze and understand the distinctive structure of each output clustering. To ease this process, we consider diverse clusterings embedded in different subspaces, and analyze the embedding subspaces to shed light into the structure of each clustering. To this end, we provide a two-stage approach called MISC (Multiple Independent Subspace Clusterings). In the first stage, MISC uses independent subspace analysis to seek multiple and statistical independent (i.e. non-redundant) subspaces, and determines the number of subspaces via the minimum description length principle. In the second stage, to account for the intrinsic geometric structure of samples embedded in each subspace, MISC performs graph regularized semi-nonnegative matrix factorization to explore clusters. It additionally integrates the kernel trick into matrix factorization to handle non-linearly separable clusters. Experimental results on synthetic datasets show that MISC can find different interesting clusterings from the sought independent subspaces, and it also outperforms other related and competitive approaches on real-world datasets. …

Fractal AI google


Fractal AI is a theory for general artificial intelligence. It allows to derive new mathematical tools that constitute the foundations for a new kind of stochastic calculus, by modelling information using cellular automaton-like structures instead of smooth functions. In the repository included we are presenting a new Agent, derived from the first principles of the theory, which is capable of solving Atari games several orders of magnitude more efficiently than other similar techniques, like Monte Carlo Tree Search. The code provided shows how it is now possible to beat some of the current state of the art benchmarks on Atari games, without previous learning and using less than 1000 samples to calculate each one of the actions when standard MCTS uses 3 Million samples. Among other things, Fractal AI makes it possible to generate a huge database of top performing examples with very little amount of computation required, transforming Reinforcement Learning into a supervised problem. The algorithm presented is capable of solving the exploration vs exploitation dilemma on both the discrete and continuous cases, while maintaining control over any aspect of the behavior of the Agent. From a general approach, new techniques presented here have direct applications to other areas such as: Non-equilibrium thermodynamics, chemistry, quantum physics, economics, information theory, and non-linear control theory. …

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Source: https://analytixon.com/2021/06/15/if-you-did-not-already-know-1423/

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KDnuggets Top Blogs Rewards for May 2021

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KDnuggets Top Blogs Rewards for May 2021

We announce the winners of the first KDnuggets Top Blog Rewards Program.


Top Blog RewardsCongratulations to winners of KDnuggets Top Blogs Reward Program for May 2021, which will share the total amount of $2,000 (USD) according to the unique page views in the first 21 days starting with the day of publication.

  1. Vaex: Pandas but 1000x faster, by Ahmad Anis (original)
  2. Data Preparation in SQL, with Cheat Sheet!, by Stan Pugsley (original)
  3. A Guide On How To Become A Data Scientist (Step By Step Approach), by Aditya Agarwal
  4. Top Programming Languages and Their Uses, by Claire D. Costa (original)
  5. Essential Linear Algebra for Data Science and Machine Learning, by Benjamin Obi Tayo (original)
  6. Charticulator: Microsoft Research open-sourced a game-changing Data Visualization platform, by Josh Taylor

We started this program to encourage more high-quality and especially original (unpublished) contributions to KDnuggets.

For each month, starting in May 2021, we will determine 6 most viewed blogs published on KDnuggets that month (excluding blogs by KDnuggets Editors Matthew Mayo and Gregory Piatetsky), and will distribute $2,000 (USD) among the authors of these top blogs. If a blog has multiple authors, we will send the payment to the first author and it will be their responsibility to distribute it. If the author declines the monetary reward, the amount will roll over to the next month rewards.

While we appreciate and publish the reposts, the goal of this program is to get more great original publications, which will be rewarded at the rate of 3X the reposts. Note: An original submission first published on KDnuggets may be reposted elsewhere two weeks after KDnuggets publication, provided there is a link to KDnuggets blog and text “Originally published on KDnuggets”.

Here are the details on KDnuggets Top Blogs Reward Program .

To submit a blog to KDnuggets, please follow the submission guidelines.

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Source: https://www.kdnuggets.com/2021/06/top-blogs-rewards-may.html

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Americans are curious about electric trucks, but low cost, durability come first – Reuters/Ipsos poll

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By Tina Bellon

(Reuters) – While most Americans expect electric vehicles eventually to dominate the nation’s roadways, many have greeted the first battery-powered models with skepticism, expressing concerns about the potential costs and inconveniences of owning such vehicles, a Reuters/Ipsos poll showed.

Automakers have already recognized the challenge and said they plan to market future battery-powered models by touting their performance and long-term cost savings over environmental benefits.

Vehicle manufacturers need to win over more rural Americans and Republicans, with the survey showing those groups express less enthusiasm than others for electric vehicles.

Vehicle electrification, particularly of the most popular large, fuel-intensive light trucks and SUVs, has become a central part of U.S. efforts to reduce greenhouse gas emissions to combat climate change. In the Reuters/Ipsos national poll of around 1,005 adults from June 3-4, 67% of all respondents agreed in a bipartisan consensus that pickup trucks are the American way of life, underscoring the focus on electrifying those vehicles to reach climate goals.

Rural consumers in so-called red states or Republican strongholds are a key demographic for pickup trucks, the auto industry’s most profitable vehicle segment, challenging automakers to navigate an electric future without alienating those customers.

Several automakers, including Ford Motor Co and General Motors Co, are planning to release all-electric trucks in the coming years. But no electric pickup truck is yet available, which means consumer attitudes about them are largely based on second-hand knowledge.

Graphic-What do you want in a truck? https://graphics.reuters.com/AUTOS-ELECTRIC/SURVEY/qzjpqrgynvx/chart_eikon.jpg

A majority of 65% agreed that electric vehicles are the future of the auto industry, the poll showed. While there were clear divisions along party lines – with 53% agreeing among Republicans, compared with 78% among Democrats – the issue is less partisan than other contentious U.S. political topics.

Nearly half of Americans – 46% – believe EVs are not worth the cost, the survey showed, with opinions again reflecting a political divide. EVs have a higher sticker price than comparable gasoline models, largely due to costly batteries.

When asked to consider buying a new truck, only a minority said they would search for one that minimizes its impact on the environment. Thirty-eight percent said they would look first for an efficient truck that costs less to operate. Another 34% said they wanted a durable truck, and only about 19% said they wanted an environmentally friendly one.

PERFORMANCE BENEFITS

Jim Richman, a window installer in Austin, Texas, who owns a 2018 Ford F-150, said he is also concerned about the reliability of electric trucks and the hassle of charging them.

“I just want to know my truck is ready whenever I need it, and also for longer trips,” Richman said, echoing a sentiment among a majority of survey respondents who said EVs generally were inconvenient because of their need for charging.

The auto industry is trying to alleviate those concerns with technological innovations, including reductions in battery costs and longer driving ranges.

GM, which plans to start selling an all-electric version of its Hummer pickup by the end of next year, said more consumers will consider EVs as they become familiar with battery-powered vehicles. GM is also trying to emphasize economic benefits of going electric.

“We have a tremendous opportunity to help consumers understand that benefits of driving electric aren’t just related to the environmental benefits, but performance and capability that EVs offer,” said Darryll Harrison, a GM spokesman.

Researchers expect EVs to reach price parity with fuel-powered counterparts around 2030, and EVs also provide long-term cost savings due to lower maintenance costs and the lower cost per mile of refueling with electricity instead of gasoline.

Ford said its research had shown consumer demand for an e-truck, especially among younger truck owners. The company plans to release its all-electric F-150 Lightning truck next year, for which it has received some 100,000 reservations to date.

“By 2030 we expect 40% of our global mix to be fully electric and we’ll achieve that by electrifying our most popular name plates,” said Darren Palmer, Ford’s North America EV general manager.

Chris Sherman, general manager of a Ford dealership in rural Paris, Texas, said he has been surprised by the positive response to the Lightning so far.

“These are pretty much diehard gas and diesel pickup owners,” Sherman said. “Lot of people here are blue-collar, and they tow utility trailers. They want to know how much of a day’s work they can do with their truck.”

Sherman said he had so far received 10 reservations for the electric truck and that he fields up to 40 phone calls per day about it.

The Reuters/Ipsos poll was conducted online, in English, throughout the United States. It gathered responses from 1,005 adults, and the results have a credibility interval, a measure of precision, of about 4 percentage points.

(Reporting by Tina Bellon in Austin, Texas; Additional reporting by Paul Lienert in Detroit; Editing by Joe White, Chris Kahn and Matthew Lewis)

Image Credit: Reuters

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GM’s self-driving car unit Cruise to access $5 billion credit line

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BERKELEY, California (Reuters) -General Motors Co’s majority owned Cruise self-driving car subsidiary said on Tuesday it would gain access to a multi-year $5 billion line of credit with GM’s finance arm to fund its purchase of Origin vehicles starting in early 2023.

“This bumps up Cruise’s total war chest to over $10 billion as we enter commercialization,” Dan Ammann, chief executive of the Cruise unit, which also counts Softbank and Honda as minority investors, said in a blog posting.

Self-driving startups are racing to build warchests to develop and scale up technology, an expensive and time-consuming process.

This past month, General Motors began assembling the first of about 100 pre-production Cruise Origin all-electric vehicles to be built this summer for validation testing, Cruise said.

Cruise, which has been testing driverless GM Chevy Bolt electric vehicles in San Francisco, plans to commercialize the technology in the densely populated city “in months, not years,” spokesman Ray Wert said.

Reuters last month reported that Cruise and rival Waymo, a unit of Alphabet Inc’s, have applied for permits needed to start charging for autonomous rides and delivery in San Francisco.

(Reporting by Hyunjoo Jin; Editing by Edmund Blair and David Gregorio)

Image Credit: Reuters

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