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Category: Analytics

What Should Graduates Do In a Tough Economic Situation? Imarticus Learning Has an Answer!

Posted on by Imarticus Learning

It was discouraging for the jobseekers to learn that the global economy has received a major blow from COVID-19 outbreak, leading to a hiring freeze. Fresh graduates are among the most affected by the hiring freeze. Many of those who bagged a job through campus selection are being notified that the offer has been rescinded.

When the COVID-hit job market is seeing a surge of experienced professionals who became the victim of the financial crisis after the pandemic, freshers are struggling to find an employer who is ready to invest time to train them. Students perusing online courses are more worried about their future.

Online ClassesWith many online classes providing little mentoring or placement assistance, they are struggling to find direction among this chaos. Fret not, the future is not grim, it is just different. So, what should fresh graduates do in this crisis? Read on to find the answer.

Industry Partners

Imarticus has partnered with the leading names in the market to co-create a curriculum based on preparing the students to deal with real-life problems. Enrolling in such experience-based courses give the students an edge in the market. Imarticus has a good placement record with eight out of 10 students placed in leading organisations.

Have a Clear Goal

What should you do if you do not see job openings in the target industry? The easy way out is to settle down with any job that comes your way, be it a generic one. But, is that what you want? Did you take up your favourite course to do a random job? The current situation suggests that the economic crisis is going to stay for some time. So, you need to learn to live with it, instead of waiting for everything to settle down and the market to kickstart, you need to find ways that could eventually land you on your dream job.

Take time to Introspect

The question is how prepared are you to make the most of this momentum? Are you market-ready? Are you visible to your prospective employers? Given that many skilled professionals are looking for a fresh start or a career change, you need to make sure that you mark your presence so that your resume does not get lost in the sea of applications. Well, how to do this? To get a head start, visit talent concierge services and be a part of the talent pool. Your profile will be listed and accessible to the companies who are on a lookout for talents. Imarticus has a pool of more than 100 mentors who guide the students to find a job in this difficult situation.

Plan a Strategy

Devise a plan. Figure out what you want to do, understand the most relevant experiences needed for your target role. See if you need to enrol for online study classes to build more skills. Use this time for all those time-consuming things. Equip yourself with relevant certifications. If the target role demands hand-on experience, try for internship opportunities.

Online LearningMany internship opportunities offer a chance to convert into full-time positions. You may also consider volunteering or working for a non-profit organisation. Check for online platforms and groups where you get to interact with like-minded people who work in a similar role or the same industry. Look for open projects and try to contribute. Grow your network and seek opportunities. Look for meetups in your city and try to be a part of it. If you are confident, venture out to entrepreneurship.

Imarticus alumni platform is a wonderful place to meet like-minded professionals many of whom have already secured a job or ventured into start-ups. They are excellent resources not only to build your network but also for guidance on having the right strategy to win a job.

Being a fresher is indeed a challenge in the current situation. But with the right strategy and wise usage of time, you can overcome this crisis. Invest time in skill-building, strategizing, networking, and introspection. Find a mentor who can help you create a plan. Explore an opportunity to give back – volunteer or work for a non-profit organisation. Think out of the box and find ways to get experience in your target roles.

Here Are Some Data Science Careers Which Are Enhancing Our Future!

Posted on by Imarticus Learning

With the increasing reliance on data science by major corporations and the biggest brands, Data science is the prime focus of this decade. Data science is making our future better by enhancing our life in various ways and through various services.

There are different careers like data analysts, business analysts, and data scientists that one can pursue to contribute to this truly interesting field which has a huge effect on our lives and will affect our future in the years to come. Similarly, data science promotes and supports IT and the efficiency or effectiveness of businesses.

In this article, we will cover how data science is enhancing our future and the various respected careers with job roles that are highly in need of being filled. 

How Data Science is improving our future

There are a variety of ways that data science is improving our future; ranging from its applications in medical science to rapid accurate resolutions to troubled customers, data science is responsible for making our lives faster, safer, and smoother in general. For instance, data science is helping the health industry by allowing patients to be treated more effectively by analyzing historic data of patients.

It is also helping medical science by empowering chemical synthesization and simulating the effects of medication on affected individuals or allergies. Data science is increasing safety and cutting risk for us as well with applications in automated braking systems, AI in navigation, and automated cars, warning about industrial risks or any issue with the structural integrity of physical or digital units.

Data science makes our lives smoother by providing assistance in machine learning of customer care or service platforms which in turn give us rapid and precise resolutions. Data science powers the recommendation engines during shopping, social media and search or media recommendations by learning our behavior and global trends and then using AI to provide us suggestions.

Highly regarded Data Science careers valued by companies and the beneficiaries 

A data science course helps individuals acquire the necessary skills to contribute to this highly reputed and valuable field that works with data. 

Data Science JobsData Scientist – A data scientist helps while sourcing the data and then processing the data. Data scientists are experts in data mining and are responsible for removing the noise from the data, handling the data, modeling the data, and storing the data.

 

  • Data Analyst – Data analysts also engage in data mining, data cleaning, and then working on the data with various tools. Data analysts then analyze the data and then use predictive analytics to gain insights from the data with various tools and simulations with the help of the acquired data.
  • Data Engineer – Data engineers work with scripts for injecting data from various sources, they are involved in the modification of data, creation of data models and they work on the data with various programming languages. They also troubleshoot data problems and assist IT or software development projects.2. Business Analyst – Business analytics is highly used by organizations to gain insights from data, and then with their help, companies make business decisions based on the visual or graphical representations and predictive analytics which is backed by data. Business analytics helps businesses a lot by helping them make the right decisions which helps them cut costs or maximize profit while minimizing risk. 

 

 

  • Marketing Analyst – A marketing analyst uses analytics to find our market patterns and the user or target behavior to help companies accurately target ads and marketing promotions. Marketing analysts depend on data to figure out trends and target the relevant audiences. 

 

It is due to data science that we are able to enjoy the various forms of technology and automated or AI-powered services that are backed and powered by data science. An expertly orchestrated data science course can help in acquiring various job roles that are in need to be delegated to human assets trained extensively in data science. 

Role of Business Analysts in SCRUM and Why is a QA Best for This Role!

Posted on by Imarticus Learning

SCRUM is an agile framework commonly seen in IT or software projects, which is used in the development, delivery, and sustenance of complex products in a simple format that avoids too many roles involved in a project. Business analysts are fundamental in any project as they act as the common point of communication. This even involves taking the role of a mediator during disputes regarding the doability of requests or technical misunderstandings between team members or stakeholders.

Business analysts look after the development of the program with the other developers and also keep the stakeholders’ interests in mind. Business analysts are tasked with acting as the company as well as assisting the other team members to accomplish the requirements.

A good Business Analyst Course with Placement program prepares individuals to tackle development problems and how to handle their roles in frameworks like SCRUM. Analysts have two very important roles to play in a SCRUM ecosystem.

Business Analyst Training with PlacementThe role of a Business Analyst as a product owner 

In this role, a business analyst is expected to take ownership of the project acting as the company. The business analyst is tasked with communicating with the stakeholders and the company to tackle product decisions with assistance from other developers who are part of developing the program.

This role also involves creating an actionable roadmap that can be followed and setting milestones for the development of the program. The business analyst has to take the necessary steps to align stakeholder expectations and the delivery capabilities of the team.

The role of a Business Analyst as a team member

Business analysts also play the role of a team member where their primary function is to support and assist the other team members. Business analysts create project backlogs and take up many responsibilities like working with the main programmers and testers.

They are involved with the creation and product writing of the project till the sprint demo. And, even after the program can run successfully, business analysts test the products as a product owner and end-user to determine if it checks all the boxes of a successful program. 

Why does a QA fit into this role so well?

Someone who is in charge of Quality Assurance tests the programmed solution for problems or stakeholder requirements by marking down its technical properties and testing it. A Business Analyst is supported by the QA in checking the functionality of the product, confirming the maintenance of protocols, and reviewing the product from the point of a customer who would finally be using the product.

In this phase, the QA ensures if the product clears all the quality checks and maintains the basic foundation framed by the product writers initially. A good business analyst program arms business analysts with the ability to run quality assurance for these projects to finalize the product completion before it is finally shipped to the end-users.

Conclusion 

Business analysts are highly necessary for most software development projects to act as the point of contact between stakeholders and developers. A reputable business analyst training program such as the one Imarticus Learning offers which leads to a Business Analyst Certification Courses recognized by corporations can prove very beneficial for budding analysts who wish to join big corporations and get involved in high-profile development processes. If you have any queries on this topic, you can put down a comment below and we will get back to you!

Interesting Puzzles To Prepare For Data Science Interviews !

Posted on by Imarticus Learning

A Data science career is a lucrative opportunity with many young professionals opting for it. With the easy accessibility to data science courses, the number of professionals pursuing it is rising. There is a huge demand for expertise in this area and it has been voted as the best career by Glassdoor in the United States.

Though there is a need for professionals in this field, it is often not easy to get into. Organizations look for problem-solving and analytical skills in their potential employees and judge them based on creative and logical reasoning ability.

Having a different approach towards a problem and solving it in a unique way can help one stand out from the crowd. It isn’t a cakewalk to master these abilities. One has to practice and try to improve their skills. Solving puzzles is a way to test the individual’s ability to think out of the ordinary and also puts to test problem-solving skills.

The interviewers while hiring fresher especially give them puzzles to solve during their interviews. Due to the pandemic, many companies now have a stricter policy when it comes to choosing the right candidate for the job. It is challenging and the chances of selection are less compared to earlier.

Data Science Career Interview

Some are even assessing the candidates based on their coding skills. To provide an insight into what is in store for the candidates, below mentioned are some of the commonly asked puzzles during a data science job interview.

  1. There are 4 boys A, B, C, and D who are supposed to cross a rope bridge. It is very dark and they have just one flashlight. It is difficult to cross the bridge without the flashlight and the rope bridge can only stand 2 people at once. The 4 boys take 1, 2, 5, and 8 minutes each. What is the minimum time required for the four boys to cross the rope bridge? 

Sol:

This is a question that is most repeated and has an easy solution. A and B are the fastest boys and can cross the rope bridge first. They take 2 minutes. B stands on one side and A returns with the flashlight in 1 minute. So the total time taken is 3 minutes. After that, C and D have to cross the rope bridge. They have taken 5 and 8 minutes each. The total time taken is 8 minutes.

When we add the time taken by all, it is 3+8 which equals 11 minutes. C and D stand on the other side and B takes 2 minutes to return. Hence the total time that is taken by all is 11+2 which equals 13 minutes. At last, A and B will cross the rope bridge and will take 2 minutes and that adds the total time to 13+2 which is 15 minutes. So the time required by all the 4 to cross is 15 minutes.

  1. A person is in a room with the lights turned off. There is a table. A total of 50 coins have been kept on the table. Out of the 50, 10 coins are in the head position while the other 40 are in the tails position. The person has to segregate the coins into 2 different sets in a way that both sets have equal numbers of coins that are in the tails position.

Sol:

Segregate the coins into two groups, one with 10 coins and the other with 40 coins. Turnover the coins of the group that has 10 coins

  1. A bike has 2 tyres and a spare one. Each tyre can only cover a distance of 5 kilometers. What is the maximum distance the scooter will complete? 

Sol: 

To simplify the problem, we will name the tyres X, Y and Z respectively. 

X runs 5 kms

Runs 5 kms

Z runs 5 kms

Initially, the bike can cover a distance of 2.5 kms with tyres X and Y

X=2.5 kms, Y=2.5 km, and Z=5 kms

Take off tyre X and ride the bike with YZ another 2.5 kms

Remaining X= 2.5, Y=0 and Z=2.5

Take off tyre Y and ride the bike with XZ another 2.5 kms

Remaining X=0, Y=0 and Z=0.

Hence, the total distance covered by the bike is 2.5+2.5+2.5 = 7.5 kms

The more an individual practices such puzzles, the better the chances of landing a data science job.

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Analytics & Data Science Jobs in India 2022 — By AIM & Imarticus Learning

The Rise Of Data Science In India: Jobs, Salary & Career Paths In 2022

Why It Is Right Time To Pursue A Career in AI, ML and Data Science?

Posted on by Imarticus Learning

Introduction

The world is all set for a digital transformation. New technologies are disrupting how business is being conducted on a day-to-day basis. Among the most notable of these technologies are Artificial Intelligence (AI), Machine Learning (ML), and Data Science.

These technologies are constantly restructuring the landscape of different economies throughout the globe, as it provides tremendous career opportunities. Moreover, these technologies are also interrelated which gives an individual a chance to build a holistic, well-paying, and satisfying data science career.

Career In Data ScienceWhy now is the Right Time?

We are living in the age of the fourth industrial revolution where everything is expected to be data-driven. Moreover, the pace at which the volume of data is growing is simply astonishing.

According to an IBM survey, 90 % of the data available has been created in the last two years. Technological devices like smartphones, tablets, and laptops have revolutionized the way users interact with the internet, and this number of users is also increasing at an exponential speed.

Now, accumulating data is not enough. An analysis of data is required to produce insights that can help in the curation of actionable results. This is exactly where the tools of AI, ML, and Data Science become relevant. These tools leverage various techniques from mathematics, statistical modeling, data engineering, data visualization, computer programming, cloud computing, etc.

To extract the insights from data collected by an organization. Now, this insight forms the basis of strategic decision-making in any organization. It is used to create targeted ads, augment customer experiences on company websites, reduce costs, forecasting demands, and so on. Therefore, the application of predictive algorithms like AI, ML, and data sciences are pervasive throughout different functional domains.

Again, these tools are used across different organizations as well. Governments, Corporates, Brands all are leveraging the advancements in technology to create an entire automated, data-driven ecosystem. Therefore, naturally, there has been an upsurge in the demand for data science courses in India and data science jobs across industries and functions. It is estimated that in India close to half a lakh positions have opened up.

Data Science CareerFrom an Indian context only, a typical data scientist is expected to receive a salary of around INR 9 lakhs p.a. Similarly the salary figures for AI and ML engineers would lie at around INR 5.5 lakhs p.a. and INR 11 lakhs p.a. respectively. Therefore, a six-salary figure makes a career in these disruptive technologies even more attractive.

With the pandemic changing the operation models across industries and functions, it can be safely assumed that technology is going to become even more relevant. Data Science, AI, and ML have a steep learning curve more and more organizations are adopting newer and agile techniques.

From expensive platforms, SPSS, SAS, etc. and organizations are now moving to open resource platforms like python and R. Therefore, technology is no more the future anymore; it is here and those who are passionate about it can find a lucrative career opportunity in AI, ML and Data Science.

Data Science and Analytics Career Trends for 2021!

Posted on by Imarticus Learning

A career in data analytics and/or data sciences is presently in extreme demand. This is due to the need to optimize new modes of data collection to identify large-scale problems and find solutions in a world after Covid-19, despite a minor drop in job openings at the start of the worldwide lockdown.

data analytics career

There are several trends that one must look out for if he/she wishes to pursue a career in data sciences and/or data analytics, including and beyond ones that involve adjusting to the ‘new normal.

It can be argued that 90% of data that is generated and collected were over the past 3 years. The demand for data science and analytics is therefore only going to grow in demand, at least for the next 10 years (and probably more). To ride this wave of opportunities in jobs and research and beyond, one must keep up with career trends relating to these fields.

What are the trends one must keep up with to enter a career relating to data?

  1. Understanding Data Collection

One must take a look at the avenues which entertain the possibility of data collection – preferably in new, never-before-seen ways. One may look to his/her area of expertise and collect data on it while combining newly learned data management skills to become a data analyst and/or scientist. This may definitely be aided by undertaking programs like data analytics courses at Imarticus learning.

  1. Analytical Problem Solving

In addition to hands-on experience, data analytics online learning may cover various fields relating to data. One must learn the basics like spreadsheet management in order to tabulate data more efficiently for analyst work.

Data Analytics Career

It is a useful skill to know what to recognize as possible data and convert that into an absorbable format, which will ensure later calculations, problem identifications, and solutions.

  1. Understanding Data Management Tools

If one is more interested in being a data scientist, then he/she must work to observe trends in big data. This involves learning big data management tools like Hadoop to find newer frameworks to collect, store and make sense of data. With earning SQL and no-SQL programming in addition to managing databases, one may find new problems to solve, whether for research or for aiding a business (or one of the myriads of other uses).

  1. Machine Learning

This is further aided by mastering other tools like machine learning and artificial intelligence. There are various tools that one may incorporate into his/her data studies, be they included in basic data science and/or data analytics courses or not. Undertaking this endeavor will allow one to master various avenues for finding and exercising ideas, which the world will go on to greatly benefit from.

  1. Communication

A possibly surprising trend that can be observed in regular data analysts and data scientists is the presence of soft skills. Someone dealing with data is required to regularly articulate and advertise new ways of improving things in his/her burgeoning field. Skills like effectively communicating one’s ideas and building useful chains of interpersonal relations go a long way in aiding the career of a data analyst and/or scientist.

  1. Artificial Collection of Data

One must find ways for his/her data collection and processing models to work without his/her presence. This process involves training replacements – both artificial and human. Ideally, a data scientist is expected to design systems that function without his/her interference, not only to undertake routine tasks but also to identify new problems and calculate possible solutions. A noted data trend is the undertaking of this process.

Conclusion

In conclusion, one can say that he/she must observe several trends relating to data on a regular basis, to adapt and grow into the self that can make a huge impact on this frontier field.

Data Analytics CareerData science and analytics are making strides in the tech market, and it is clearly the future. So, a career in data analytics can be really fruitful in the long run.

What is the Difference Between SAFe and Scrum Master Certification

Posted on by Imarticus Learning

What Exactly is Scrum and What is Scrum Master?

Scrum is a structure that helps build team working habits. It encourages teams to use past experiences to learn from them, self organise when working on an issue and analyse both their losses and wins in order to improve. This agile management device defines a set of meetings, instruments and roles which work together in order to help teams in structuring and managing their work.

Scrum masters help in facilitating scrum and is an agile framework that is lightweight. It focuses on time sensitive iterations called sprints and as a facilitator it acts as almost a coach to the team called servant leader. Scrum leaders must consider opportunities that will help the team improve its quality of work while remaining committed to the scrum’s foundation values.

What is Scrum Master Certification and What Does it Entail?

Scrum master certification helps people understand what good scrum is as per official scrum guides. The basis of the certification is the scrum guide. The certified exam for this is lightweight with 100 multiple choice questions drawn over a span of 2 hours and is taken after scrum master training.

What is SAFe?

SAFe happens to be a globally leading framework used to scale Agile across enterprises. It is designed to increase efficiency by driving a faster time to market ratio thus increasing productivity. Lean-Agile transformation is a combination of leadership engagement and education as well as training. Its role-based curriculum assists enterprises in bettering results.

What is SAFe certification and what does it entail?

This certification assists in resolving coordination issues in three stages:

1. Introducing management at an executive level thus passing on available budgets onto different value streams.
2. Organising the value stream within the company in order to generate various products and distinct services.
3. Encouraging more roles and practices at different stream levels.
Its basis is the website and training material provided by them in order to cover a larger span of content than just plain scrum.

The SAFe examination is a lot harder to clear considering its huge course content and highly advanced level of certification. There are 70 questions with a requirement of at least 75% to clear the exam. The exam like the scrum master examination requires training and preparation.

The differences in scrum master certification and SAFe certification are as follows:

Scrum master certification:

  1. It is structured and curated for a single team.
  2. It has three primary operational roles – Scrum Master, it’s development teams and the owner of the product.
  3. Usually four ceremonies are part of this. They are, daily scrum, stand-up meeting, deciding plan and review. This helps in reflecting on issues and rectifying them.
  4. The scrum master course for certification usually fits into one framework.
  5. It is mostly self-organised with cross-functional teams being co-located.
  6. It is more of a foundation level certificate. It can be used as a stepping stone to be able to proceed to more complicated certifications like SAFe.

SAFe certification:

  1. This could entail a team of a hundred to even a thousand members for turnkey projects.
  2. It is used majorly in scaled project environment groups.
  3. The roles covered here, under SAFe, are beyond scrum master certification. Its roles may even go as high as portfolio and program management levels.
  4. It is not just restricted to team level but can cover ceremonies beyond that as well.
  5. Covering a combination of multiple frameworks, it proves to be advanced and versatile.
  6. It can be located in a multitude of sites due to its time flexibility allowing it to be found in different time zones as well. They can thus be called a centralised and decentralised decision making environment.

With Jobs at Risk, can a Career in Big Data Keep You Safe?

Posted on by Imarticus Learning

Data powers the information economy just like oil powers industrial economy. No wonder they say, “data is the new oil”. A critical asset to many industries, data science and AI changed the way information is gathered and processed. Even when COVID-19 hit the global economy, leading to job cuts and hiring freeze, data science remained unaffected.

While companies do not debate on the importance of data science, collecting and storing the huge volume of data was a big challenge. With limited capabilities, companies had a big struggle to maintain and process data. However, AI and cloud-based technologies provide a solution to this problem. These technologies have created better job opportunities for data professionals than ever before. If you are aspiring for a data analyst career, there isn’t a better time than this.

Why Big Data?

The world is consumer-centric and will remain so despite the hard hits on the economy. Consumerism is the driving force that creates revenue, and job opportunities. From healthcare to e-commerce, all industries are data-driven. The data requirement changes from one business to another, from one company to another. But the enormous amount of unstructured data can be collected using various tools and techniques, organized and structured according to the business needs.

No matter the business is consumer data is vital to all businesses. The tech giants like Google, Amazon etc, and the social media giants like Facebook have been using the potential of data to achieve a competitive advantage over their rivals. And the result is pretty much evident. They are far ahead of their competitors.

What is common among all of them is that they collect large swathes of data regarding their customers – right from what products they buy, which products they ditched after adding to the cart, which posts get better engagement, how long does a person spend time on their webpages – every single move of their customer after arriving on their website is tracked, processed and analyzed to make better business decisions.

The global health crisis saw the extensive application of data, how it can be used to manage a crisis better. From contact tracing, health screening and mitigating the spread. Many apps were developed to help contain the spread, leveraging the GPS to identify the COVID-19 hotspots.

The Increasing Demand for Data Scientists

COVID-19 has indeed changed the way the world functions. With more people staying indoors, individuals flocking the internet also increased. From work to shopping, everything is being done online. And this has increased the requirements for data scientists. While many companies struggle to acclimatize and manage their current employees logging in from a remote place, Tech firms are out with a pressing need to recruit more talents.

With more students and professionals active online, the need for online tools and platforms is growing, and this has led to the demand for an intense expansion of their talent pool.

AI and cybersecurity talents are the most coveted as many companies need technical support in digitizing their businesses. This calls for the improvement of data security measures and to enhance automation to reduce the on-site manpower.

Firms that rely on AI-powered software and those which provide such platforms are on a lookout for technical talents including software engineers and data analysts. Furthermore, financial services companies are also gearing up to become market-ready when the economy reopens. They have started headhunting for people with risk management and data analytics skills to cater to the recent spike in digital banking and online payments activities.

Data Science Online CourseData science is one of those areas not affected by COVID-19. In fact, the pandemic and the enforced stay-ins have resulted in an increased demand for data scientists. If you are a new graduate, take this opportunity to make the most out of the current market situation.

Enrolling in a Big Data Analytics Course could help you land on a lucrative career in data analytics and big data.

Stay Competent with most In-Demand Data Science Skills!

Posted on by Imarticus Learning

What is Data Science?

The Science of combining capital processes, algorithms, and many such best tools to collect, manage and analyze the most important data to make business decisions is Data Science.

Who is a Data Scientist? 

A computing professional beholding the skill of data collection, data storage and management, and data analysis enabling the organization to make data-driven decisions quickly are Data Scientists.

 In-Demand Data Science Skills

Some of the most In-Demand Data Science Skills are:

Understanding of Math & Statistics 

Online Data Science course in India is all about extracting the required information from the data. A depth understanding of mathematical probabilities and statistical methodologies helps in data analysis.

Data Science SkillsThe majority of the data science models are built using one or more, known or unknown variables. Thus, the in-depth understanding of multivariate calculus is the key requirement to develop Machine Learning models.

A detailed understanding of functions such as Logit, Cost, rectified Linear unit, Step, Sigmoid, etc. is very much required to deal with the large data. Apart from these functions, the detailed understanding of Matrix algebra.

vector Algebra and Differential and Integral calculus help the Data Scientists to develop and understand the systems at a faster pace.

 Programming Skills for Data Science

In order to achieve the objective to transform the raw data into business insights, Programming skills plays a crucial role. Among all the programming languages, the go-to languages are Python and R, Python being the lingua franca in the data science field.

Skill to wrangle the Data

The process of removing imperfections from the raw data to get the data that can be easily analyzed is known as Data Wrangling. The entire process includes acquiring the data, combining the data with relevant fields, and cleansing the data. In short mapping the raw data from one form to the other to set up the data to get business insights.

Management Skills

Database management is a prerequisite of Data analysis. The basic requirements for a Database Management System is the family of programs to edit and manipulate the data and the operating system to provide the specific data.

Data Science Career 

The special skills set will definitely make you stand out from the crowd when the field and hence the number of jobs in the market are increasing at a faster pace.

Data Science Career Job Requirements Average salary
Data Scientist ·      Data collection and organization

·      Find the pattern in the data to help the strategic business
decision

  

$139,840
Data Engineer ·      Batch Processing of the database

·      Build and maintain data pipelines

·      Make the information available to the Data Scientists

 $102,864
Machine Learning Scientist Research for the new data approaches and deep learning techniques. $114,121
Machine Learning Engineer ·      Create data funnels

·      In-depth understanding of statistics and programming

·      Designing and developing machine learning systems

 $114,826
Data Analyst ·      Transform the large Database to meet the purpose.

·      Prepare the reports to facilitate the decision-making process by communicating trends and insights from the data.

 $62,453
Business Intelligence Developer ·      Design and develop the strategies to make the specific information accessible for business decisions in lesser time.

·      Facilitate the system understanding to the end-users to use the data effectively

 $81,514
Statistician ·      Facilitate the Data Collection process.

·      In-depth Data analysis

·      Data interpretation

·      Identify the relevant trends from the data

·      Design data collection processes

·      Advise the overall organizational strategy

 $76,884
Applications Developer ·   Keeping track of the applications used in the business and internal interaction

·   Design the overall process flow of applications with the inclusion of development of user interface components etc.

 $113,757

 

 Average Salary data is taken from https://www.glassdoor.co.in/Salaries/data-scientist-salary

10 Data Analytics Myths that Can Hamper Your Business Data!

Posted on by Imarticus Learning

Myths are a waste of time; they prevent progression – Barbara Streisand

In addition to making conclusions about the data, the science of evaluating raw data is what we call data analytics. Many techniques of data analytics and procedures have been converted via automation into mechanical operations and algorithms that operate over raw information for use by humans.

It is a booming field and many young and ambitious professionals are opting for data analytics courses. Many universities are offering data analytics courses online.

Due to its complexity and distinctive language, many amateurs don’t understand it and are hence oblivious of its activities in the backend. Its insignificance has led to the emergence of good and bad myths that have forayed into people’s minds. It can discourage any organization from effectively capitalizing on data analytics since they treat the myths as reality.

Here are the 10 data analytics myths debunked.

  1. It contributes to new findings: Theoretically, data analytics helps in finding significant data, and practically it helps in making some important decisions. Reaching new findings with AI via data analytics is untrue.An accurate understanding comes from the gathered and modeled data, and evidence is collected that proves to refute the theories. Data analytics should be used as a valuable platform for learning.
  2. It is time exhaustive: Some market leaders are of the view that using data analytics in a sensible manner is too time-consuming. One should check for answers which will align with the existing networks and then provide a complete view of the revenue-driving activities and provide execution services. In less time, the right software tools will help extract data insights
  3. It needs an exorbitant amount: The misconception that data analytics is a costly affair prevents many companies from effectively leveraging it. In fact, a solution for data analytics can be very functional and cost-effective, it is all based on the type of solution needed.
  4. Value can only be derived if an individual is an analyst: Another misconception is the above. All the credit goes to the pathbreaking development in the fields of automation along with AI for enabling the process through which anyone can avail an insight into the data information and quickly transform this knowledge into effective business decisions.
  5. Data is the force behind every business: Not all companies have data as their driving force. When the business offering makes sense, only then data is important. It is necessary to concentrate on the information, whether it is important to the company, and then join the battle, if not, keep concentrating on important progress.
  6. Bounce rates – useless to keep track of it: It is the perception of some company heads that keeping a record of bounce rates serves no purpose. The logic behind it is, these figures are usually inaccurate, and the real value is not given by the data.In reality, the bounce rate is important in increasing the SEO value and gives an indication of the consumer’s understanding of the said business, aiding them in identifying the faults responsible for people making an early exit from their site.
  7. Decisions made by machines are impartial: It confirms the already existing social biases, transforming into a “black box,” without any means of describing the logic behind choices. When the organizations are asked to explain decisions, they aren’t in charge of the manner in which models are designed, rendering them insecure and accountable.
  8. The loss of jobs is directly related to data analytics: This is a common misconception that data analytics connects to AI and that further transpires into job loss. Data analytics is akin to a business tool that produces jobs and productivity and reduces waste.
  9. More data is key: Another prevalent myth is that the more the data, the better it always is. The most important thing is that data has been well-sourced, is reliable, and also meaningful. As they always say, quality is better than quantity.
  10. Analytics runs your business: An organization cannot expect their business to grow and flourish only with the help of data analytics. It’s also about building a rapport with their customers and understanding their needs. It also depends on their processes and their products. When an organization incorporates better insights into its business processes, it can add more value.
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