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Category: Analytics

Ways To Use Artificial Intelligence In Education

Posted on by Imarticus Learning

Ways To Use Artificial Intelligence In Education

Do you know that AI is very present in all our lives and has pervaded almost every space? Not just the imaginary humans with chips portrayed by fiction writers and science fiction movie makers but just look around.

Google searches, automatic sensors for reversing your car, automatic lens adjustments and light settings for those perfectly timed selfies, Google maps to take you straight to your destination, MRIs to detect those illnesses you never thought you had, multiple-choice answer sheets scored automatically on online learning sites, paying bills online, that favorite app you just downloaded and everything I between. They all run on the artificial intelligence courses of the self-learning algorithms of machine learning help make machines truly aid to human thinking through deep learning and neural networks.

Though AI has actually taken over most of the human tasks, they are still a long way off from replacing human beings and the one area where they have tremendous application potential is in education. Let’s reiterate that the basic aim of artificial intelligence courses and neural thinking is not to replace humans but to help them with repetitive tasks and data sifting far beyond the limits of the best human brains. So, in the future, AI and humanoid robots will not replace teachers. But they will transform how we learn, and what to learn and go a step further by helping us learn. That includes the teachers too who are constantly learning too!

Why AI matters in education:

Let us explore how AI is going to bring its benefits to the education experience of the future. The class sizes keep increasing with compulsory education and teachers are often facing many challenges in giving attention and help to the large numbers of students. A big challenge like this has been simplified by incorporating computer programs that allow each student to follow his own pace and learning curve. Individualized learning modules can help find knowledge gaps and personalize the learning materials to fill in the gaps.

Teachers can now get truly involved in teaching and rectifying the lacunae in the learning process. Besides, the teachers can also get recommendations on how to rectify the issues, what learning materials to use for personalizing the process and much more to help herd the students towards the right levels of comprehension and skills required. This could also be used for learning processes of differently challenged students.

The newer methods of experiential learning at educational institutions use advanced techniques of AI, machine learning and deep learning in instructing and teaching like chatbots and learning bots. A differentiated AI style of learning deals with the most effective style to help the student learn. Adaptive artificial intelligence courses based learning curates the learning exercises matching them to the student’s needs and knowledge gaps. Competency-based AI tests aid the students to gauge their learning levels and progress from thereon. Using all these three types of learning AI can test how well the students can adapt their learning to applications of it and thus promote the progress of students based on individual interests.

The benefits:

Some of the benefits of artificial intelligence courses that can be harnessed are: 

1. Grading, scoring, and such repetitive tasks can easily be handled by AI.

2. Personalization of educational software can be need-based and adapted to individual learning curves.

3. Lacunae and learning gaps can be predicted and rectified with suggestions for learning materials and courses needed to improve.

4. Tutoring through subject-specific learning bots, online self-paced courses etc can support students.

5. The feedback route is almost instantaneous and can be gainfully harnessed by both educators and learners.

6. AI has changed the way we search for and interact with data. Just Google for information on anything and everything is what 95% of the people do to find information.

7. AI will make teachers more effective and ever-learning educators.

8. AI will develop human skills and make trial-testing-and-error learning the norm.

9. Data harnessing and empowerment will change the learning experience using AI to find, support and teach students.

10. AI can offer both offline and online resources which will alter where we learn, how and who teaches them and help apply to learn to basic implicational skills.

Conclusions: 

What do you think would be the results of AI in education and the learning process? Yes, the education field is going to be very different from what we now see it as. Skills in learning applications will count for more. Jobs will be linked to skills and not degrees. Certification will emerge as a measurable tool of skills. And, if you want to explore more, why not do artificial intelligence courses at the reputed Imarticus Learning institute?

What Machine Learning Has To Do With Your Personal Finances?

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What Machine Learning Has To Do With Your Personal Finances?

Machine learning is a subset of AI technology that develops complex algorithms based on mathematical models and data training to make predictions whenever new data is supplied to it for comparison. Artificial intelligence is the ability of machines to simulate neural networks and human intelligence through machine learning courses without the use of any human intervention or explicit programming.

Though these two concepts that always go together have been around for ages, the past two decades have seen a phenomenal rise and exploitation of benefits of ML applications.

Let us explore some applications in real-life in the financial services area where they have made huge differences in customer service, fraud and risk management, and last but not least personal finance.

Examples in Customer Service:
Chatbots are the latest feature of financial services being deployed to aid and automate and reply when asked frequently asked questions, common customer service answers and requests, help in bill payments, provide information on services and products and more.

Since they work with NLP-natural language processing they understand the query and answer appropriately. But there are instances when the scenario does not fit the scripted questions and the conversation is beyond their comprehension.

ML is important to teach the chatbots in customer service to assimilate data from interactions where the AI can self-learn how to respond in the future based on the experience they gather. Obviously more the interactions, the better they get.

They are also capable of recognizing emotions like frustration, anger and so on where they can diffuse the tensions by transferring to a live customer service agent for further help or resolution. Often they up-sell products, introduce the newer services and help in transactions like making automated payments.

During the course of such interactions, they can also pick up customer behavior trends like the possibility of defaults due to cash-flows. Imagine how satisfied a customer would be when it is the due date for payment, the account is bereft of money and the chatbot work efficiently offers a different due date, a short-term loan or a customized payment plan.

That’s just a small example of the chatbot and its machine learning courses enriching the customer or user experience.

Examples in Personal Finance:
ML comes to the aid of financial institutions by specializing in the service of customers needing applications for budget management, offering guidance and highly targeted financial advice. Such apps are made for mobile devices and allow their clients to track their daily spending.

Using their innate ability to spot trends they can help with budgeting, saving and investment decisions and plans by watching and learning from the client’s spending and purchase patterns.

Ina real-life example a leading bank spotted the trend of people from a certain segment facing problems with their cash flow and using their credit cards for late-night transactions and withdrawals. By flagging such abnormal behaviour it was found that the segment faced unduly low-interest rates in their savings accounts. Based on such foresight the bank not only improved its savings rates but it also offered the segment increased credit limits to restrict defaults on payments.

ML intelligence worked very well since the bank retained its customers with such an offer and also saw an increase in its savings accounts deposits.

Examples in Fraud and Risk Management:
In the fields of risk and fraud management the daily number of transactions to be scanned, are very large and involve huge sums of money. In modern times online payments have emerged as an ideal spot for fraud perpetration. Paypal the market leaders, have employed machine learning courses specializing in risk management and fraud detection and using Big Data, complex neural networks, and deep learning capabilities. Any abnormal behavior is flagged and forms a sandboxed risk queue within milliseconds.

The cybersecurity challenges are confrontable by smart ML algorithms. The detection of phishing attacks is dependent on the algorithm being able to easily compare the original and fake sites for logos, visual images, and site components. T

hey can also detect unusual behavior once they are trained on recognizing normal patterns on a profile or account. A red flag is immediately raised and the user is asked to verify the transaction.ML is also used in risk scoring, assessing defaults in payments, automating credit scores and compliance issues, assessing loan applications and every transaction in between.

In conclusion:
Machine learning is not restricted to any one field. However, the applications can get very complex and extend far beyond these few examples. ML helps in better security, increasing operational efficiency and delivering better customer service or user experience.

If you would like to learn more, then do the machine learning courses at the Imarticus Learning Institute where technologies of tomorrow are taught and skilled for today.

Is A Machine Learning The Next Step Of Smart Learning?

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Is A Machine Learning The Next Step Of Smart Learning?

2015 was rife with stories of ML and self-driving cars. Again a decade ago people were abuzz with robots doing the repetitive tasks, and human intervention being all about seasoned judgment for complex tasks. And then, cars were self-driven and computers really proved that they were fast approaching the machine learning course of human intelligence with self-learning algorithms and AI taking over a data-driven world.

Both AI and ML started with helping the human coded programs helping computers spot data patterns and inform algorithms which made foresight, insights, decisions and data-driven predictions. And then, the volumes of data became huge and machines needed a machine learning course to be able to help humans with cleaning and sorting the data.

 

So self-learning and deep learning algorithms soon taught the AI-driven computers to get smart and self-learn. As data became larger, their ability to accurately parse and clean data and provide insights increased. And so, we developed new self-learning ML algorithms which are the latest weapons against terrorism, cybersecurity, climate change, and cancer applications.

The Master Algorithm authored by Pedro Domingos, claims machine learning is the new basis and infrastructure for all applicational algorithms. He described it as the Higher Education switchboard. When data privacy became an issue in the UK in 2014 the US K-12 dialogue led to concerns in over-testing and by the end of the year, more than a hundred vendors of EdTech voluntarily signed the pledge for data privacy.

The series on SmartParents led with the argument that personalized learning is data-based and that parents with access to such data should decide on the privacy of the data. The policymakers were forced to embrace both data privacy and personalization.

Today ML and Big Data techniques are part of our lives and play a big role in informal and formal education. Let us see how we can make learning smart with machine learning. Below we list the areas and resources available to parents and teachers alike for

1. Learning data analytics and applications in a machine learning course that can help track student knowledge while recommending further learning steps. Here are some resources for learning systems that are adaptive.

Ex: ALEKS, DreamBox, Knewton and Reasoning Mind. Here’s a treasure for game-based learning:  Mangahigh and ST Math.

2. Beginning learning on content analytics that is used to optimize and organize content-modules.

Ex: IBM Watson Content Analytics and Gooru.

3. Scheduling for math learning that teams students needing help with teacher resources in real-time and dynamically.

Ex: NewClassrooms which uses ML and data analytics to schedule mathematics learning sessions.

4. Scoring and grading systems to score and asses on a large scale the student answers to the computer and other assignments and assessments: The grading could be peer grading or automatic ML grading.

Ex:  Lightside by Turnitin and WriteToLearn by Pearson help detect plagiarism and score essays.

5. To identify new opportunities through tools for process intelligence which analyze both big unstructured and structured data while enabling the visualization of work-flow.

Ex: Clarity from BrightBytes provides a strength gap analysis by reviewing best practices and research to build evidence-based frameworks.

IBM SPSS  and Jenzabar are systems for ERP-Enterprise Resource Planning which help the formal higher education schools and institutions in enhancing campus security, improving financial aid, predicting enrollment, and boosting student retention.

6. In helping match schools and teachers like TeacherMatch and MyEdMatch which harmonize online the recruitments of teachers.

7. For learning data mining and predictive analytics from experts try Map patterns of expert teachers and Improve learning, retention, and application articles.

8. For a host of applications in the back office are school bus scheduling EDULOG, Evolution, and DietMaster.

Parting Notes:

There is no doubt that the earlier you learn the more skilled you become. To ensure smart learning in ML every student and faculty member must learn at the earliest the impact of ML, AI, and Big Data. No matter what the pathway your learning curve should be enhanced with skills at the earliest.

Do you want to join a machine learning course at the Imarticus Learning Academy where data scientists hone their skills in AI, Big data and ML? Their courses also include personality development modules and train you in the soft skills required to emerge job-ready and with the right skill sets.

How To Encourage Your Children To Learn About Big Data And Modern Technologies?

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How To Encourage Your Children To Learn About Big Data And Modern Technologies?

Phrases like Deep Learning, Neural networks, Machine Learning or Artificial Intelligence can be a big put-off for those parents who get easily overwhelmed by the changes in digital technology which seems to change minute-by-minute. The exponential growth of data is powering it and big data analytics courses are fast becoming essential.

This is what your children inherit and grow up in. It is crucial to have them trained early on if they need to be technologically equipped to handle their daily lives and become contributors to the growth of both the economy and society at large. There is no dearth of the ignorant in places of power who have no clue regarding the present technology let alone the future technologies that are already happening!

Every country has its share of shame and court cases on the misuse of technology which stems for a complete lack of understanding of the underlying science and principles of technology. You can change that and we shall look at certain pointers that can help you along to make the future of your kids in big data analytics courses an educated and well-equipped one.

Understanding the basics:

Kids understand concepts very easily if the examples are right. Just as they learn to walk, talk in any language, and interact with others based on their experiences of watching and doing, so also complicated concepts are simpler to explain than you may think. After all, technology has existed over generations and it is those who learned to question early that became the next generation’s Einstien or Newton.

Your involvement is vital:

One of the easiest ways to update your knowledge would be to get involved in your child’s learning. Parents are the role model on which the child bases his/her behavior. Taking an interest in the learning data analysis and how modern technology will not only help you explain the simple concepts of Deep Learning, Neural networks, Machine Learning or Artificial Intelligence but will also help you understand better and make better choices as technologies advance. Ex: Buying a smartphone today involves understanding what they can do for you with Google Assistant or Amazon’s Alexa. Go ahead and discover your gadgets.

Rewards are motivators:

The simple science of getting kids to thrive in their learning is to create a task list and reward the completion of tasks with simple child-friendly rewards like a party, movie, or treat of their choice. Starting such a system helps them inculcate discipline, cleanliness, and innovation in thinking through their tasks. Rather than play for hours on end, kids find it more interesting to learn to handle gadgets like the computer, smartphones or home theatre. They not only feel grown-up but also start skilling themselves early.

Use authentic training resources:

Teaching children to Google their questions opens up Pandora’s box when un-monitored. However, the internet has some very interesting videos on YouTube, simple beginner’s courses depending on the age of your child, websites for learning kids, games that explain concepts behind what appears complicated technology and child-friendly apps that are invaluable for both you and your kids. Why not consider a few big data analytics courses online?

Learn from mistakes:

Part of the learning lies in its being used and that’s where mistakes are bound to happen. Just like kids fall and learn to walk better, complicated subjects will come with mistakes and errors that should be treated as part of the process. The parent’s role in encouraging and handling rejection due to mistakes is just the same as in subjects like mathematics, science or any other. Just as long as the child enjoys the process and no stress is created they will learn if you are sensible about their failures.

Get Assistance:

Rather than venture into the unknown territory alone, there are ample resources that you can exploit to teach your children such as teachers, tutors, and short-term beginner courses at colleges that can help. Scour your neighbourhood for students who have done big data analytics courses and would be willing to orient your kid for a very reasonable hourly fee while keeping them well-attended to and busy learning something new.

Parting notes:

So, how can proactive parents encourage children to acquire knowledge and skills in big data and modern technologies? Well, the answer is simple. It is all about the training of the mind to form a basic skill set that is curious and learns by itself. At Imarticus Learning you can learn and also enrol your children in professional courses like big data analytics courses that help build appropriate skills in the field of emerging technology. You will be getting them a quick start in their careers that could prove invaluable in time.

Bots In Learning AI And Personalized Learning Experience

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Bots In Learning AI And Personalized Learning Experience

The class sizes keep increasing with compulsory education and teachers are often facing many challenges in giving attention and help to the large numbers of students. A big challenge like this has been simplified by incorporating computer programs that allow each student to follow his own pace and learning curve.

Since the ideal teacher-student ratio has long been overtaken, a lot of educational instructors have unobtrusively introduced AI and ML to help with self-scoring assignments, computer-aided assignments and course review modules and videos that help the learning process which tends to be different in style, pace, and manner of learning in each individual student.

However such early initiation has led to students thinking of the quickest and easiest way to beat the system. This was supposed to be a part of the personalized learning process which probably needs a review given that AI and a machine learning course have a huge role to play in the future of technologies.

Learning Bots:

The newer methods of experiential learning at educational institutions use advanced techniques of AI, machine learning and deep learning in instructing and teaching like Chatbots and learning bots.

A few examples of such learning bots are:

  • Botsify is a suite of bots that have bot assistants like the tutoring bots, FAQ bots and more.
  • Mika is a math bot tutor based on AI used widely in schools and higher education institutions.
  • Snatchbot helps administrators and teachers with templates to help customize a bot to the classroom needs and subjects.
  • Ozobot is a specialized coding bot.

AI has thus personalized the teaching and learning experience by incorporating a machine learning course for bots to enable their functioning in the field of education and instruction.

Learning supports with AI:

Individualized learning modules can help find knowledge gaps and personalize the learning materials to fill in the gaps. By so adjusting the learning rate no student in a class is way ahead or too far back on the learning curve. Since learning styles, rates and methods may vary over each student, adaptive learning scores by understanding and identifying the gap in learning and taking corrective action before it is too late.

A differentiated AI style of learning deals with the most effective style to help the student learn. Adaptive AI-based learning curates the learning exercises matching them to the student’s needs and knowledge gaps. Competency-based AI and machine learning course tests aid the students to gauge their learning levels and progress from thereon. Using all these three types of learning AI can test how well the students can adapt their learning to applications of it and thus promote the progress of students based on individual interests.

Tutoring help:

The bots have become extremely popular and the future will probably have specialized tutoring bots where the learners can ask questions and receive answers in real-time. Chatbots, tutoring bots and even bots for teachers to help score examinations, assess large volumes of answer sheets and more are being used to improve the learning and educational process. Tweaking the earlier bots have led to specialized bots that even suggest and provide resources specific to a learning style.

Administrative tasks aids:

Teaching is a challenge and scoring and grading are tasks that are repetitive and time-consuming. Multiple choice questions and online testing are AI forms of grading already in use where learning responses need not be essentially written responses. Thus a lot of paperwork and unnecessary wastage of time is eliminated.

Since bots are able to quickly analyze the responses, feedback can be near-instantaneous. Teachers can now get truly involved in teaching and rectifying the lacunae in the learning process. Besides, the teachers can also get recommendations on how to rectify the issues, what learning materials to use for personalizing the process and much more to help herd the students towards the right levels of comprehension and skills required. This could also be used for learning processes of differently challenged students.

Concluding notes:

Both bot technology and its AI technology has started the process of personalizing and improving the education system of learning. Today bots are not new to students who can exploit their benefits at will and at their own pace to learn advanced subjects. Such advancements in AI, ML and bot technologies spur demand for professionals in this emerging field which has immense potential. Would you like to do a machine learning course at Imarticus Learning and join the ranks of the highly paid professionals who face no dearth of jobs? Start today. Hurry!

For more details, you can also contact to our Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

What is Business Analysis

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What is Business Analysis

To ensure that a business runs glitch-free, its requirements and problems need to be identified, and solutions need to be determined from time to time. While techniques or processes may vary from industry to industry, the setting of tasks, gathering relevant knowledge related to the market, and techniques implemented to solve business needs is known as business analysis.

Business analysis is also conducted to understand the present state of a business, and to identify what its needs are. In other instances, business analysis means analysing requirements and coming up with valid solutions that meet business objectives and fulfill goals.

From a more technical point of view, identifying business needs and implementing solutions involve bringing about more improvement in daily processes or opting for a structural change in the organization.

How does Business Analysis Impacts an Organization?

Business analysis helps stakeholders or investors of an organization, understand more about its operations, overall structure and operating policies, who can then suggest recommendations or provide solutions to help the business achieve its objectives.

For external stakeholders, the performance of an organization is extremely important for them to anticipate their returns or have a forecasting model for possible risks. Internal communication between stakeholders and other functional departments are also better understood once a business analysis is conducted.

What is the Role of a Business Analyst?

Someone who analyses the state of affairs in an organization or business enterprise, and researches, as well as, documents its process, needs and shortcomings is called a business analyst. It is also his job go understand if a business model need a to be integrated with technology, and to what extent. To become a business analyst, a business analysis course is highly recommended.

The aim of a business analyst involves the following:

  • Understanding the structure of an organization and how operations function
  • Identifying current or potential problems in an organization, recommend and implement solutions
  • To understand the stakeholders’ aims and objectives align with the general health of the business and it’s goals as wellWhat are the various steps analysts follow during business analysis of an organization? 
  • Research- The most important step of business analysis is research. Business analysts spend enough time collecting basic information about the requirements, scope of work and business goals. It is also part of their role to understand who the stakeholders are, along with an in depth knowledge of the business history, understanding how processes work in the organization, and the existing system.
  • Identifying goals of the business and setting a scope- A business analyst has to make sure that business objectives align with the stakeholders’ expectations; in case there are conflicting expectations, he should be able to merge them.
  • An important step of business analysis is making sure that business goals are set and clear, only then the scope of business can be set, which is a go-to reference document that serves in helping people understand the current needs of a business and how they can be implemented. Before any plan mentioned in the scope is implemented, it needs to be run through investors.
  • Making a business analysis plan- to ensure the outcome meets the deliverables, a business plan needs to be put in place- from setting a customized list of deliverables to setting timelines for the same. A business analyst must ensure that the scope has been covered in the plan.
  • Understanding requirements- Once a plan has been set, the implementation team needs to understand the requirements, collect supporting information for the same, review the deliverables and decide up to what extent they are attainable.
  • Technical implementation- During the process of business analysis, often certain software is conceptualized, built and deployed on a project. Making sure that the software design is in place and fixing errors if any, is an important step.
  • Apply the solution- The most important and final step for business analysis is applying the solution to identified issues and understanding it’s results, which means identifying a way forward after the solution has been applied, determining next steps for the business, evaluating progress and communicating the results to important members in the business. This step is based on the business analyst’s own skills, and cannot be mastered at a business analysis course.

Once the process of business analysis is completed, it is expected that the business will achieve its set goals and objectives. Businesses often find better opportunities, improve their internal processes and manage effective communication with stakeholders more efficiently post a business analysis.

Also Read: Life of Business Analyst in India

Benefits of Being Certified as a Scrum Master For a Business Analyst

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Did you know that according to the twelfth Annual State of Agile report a majority of 56 percent BAs practice Scrum at their workplace? The BA is the go-to person for creating new strategic business models, business decision support measures, cost-reduction initiatives, monitoring, reporting, planning, variance analysis, and regulatory requirements, understanding KPIs, importing data, forecasting budgeting and financial analysis and all in between business needs. The BA multitasks between the core business areas while effectively liaising and functioning to provide data analysis and business intelligence. Scrum practice is a vital skill for BAs as they function in a variety of multi-demanding areas and processes. Let us just directly jump to the many benefits the BA can expect to gain with a Scrum Master Certification.

Benefits to Business Analyst

Yes, personal benefits are always the drivers to any success, qualification and career enhancement. A comparison of salaries on Payscale shows that the average salaries for Scrum Masters are 1,232,102 with a 144,028 bonus and 75,000 profit sharing. Companies like Accenture are offering 65-1,656K Rs + bonus of 60K according to Glass door.
Your course will help you learn a range of scrum-skills while providing for the best support online system as you implement Scrum with the range of other certification benefits. If you have to stay marketable you will need to be a Scrum team player, adopt an Agile mindset, and communicate well with cross-functional teams. Your Scrum Master Certification enables your ability to prioritize, judge risks, remove obstacles and glitches in the project as you function as a true blue-blooded servant leader in the Scrum Team. It is no mean feat and the certification is definitely not another academic qualification. It alters your mindset and is your personal badge of honour validating your knowledge and implementing of Scrum practices as you stand out and ahead of other aspirants in the job market.

Benefits to the Organization

The BA with a Scrum Master Certification can influence the Agile thinking of an organization and is considered an organizational asset. In the software development lifecycle, the BA plays a crucial role giving them the understanding and specifications of the software and how it should align with the business goals. With more and more companies using various Agile methodologies based on the Scrum framework it is important that BAs have scrum skills and all scrum masters have BA skills. A dedicated SM is often used to ensure the product backlog list is constantly monitored and all internal or external hindrances are obliterated to succeed in rapid sprints and marketable product releases. Thus the efficiency and productivity is enhanced greatly. Further cross-functional teams need a SM to effectively keep the project on track because of the sheer diversity of essential team member skills.
Organizations have realized the value of scrum professionals and recruit Scrum Masters, Sr Scrum Masters, a Scrum Coach, Product Managers and Product Owners with Scrum certification. There definitely is room for growth in this field!

Benefits to the Cross-Functional Scrum Team

The SM role can be that of an effective tutor, mentor and leader especially in the present demand for cross-functional teams and Scrum Agile principles implementation across the board for all industries. Your Scrum Master Certification sensitizes you on actual unique ways to handle team issues, advice team members and tackle all conceivable situations in Scrum practice.

Concluding notes:

Looking at the above benefits enumerated for a BA who learns and gains from the Scrum-framework, it is obviously a win-win situation for the individual and the organization employing them. Since the BA is an excellent buffer between the IT and the organizational needs as a whole Agile principle can definitely be used to improve productivity through rapid sprints and releases instead of running into long projects and budget constraints for lack of iterations. Not just the organization benefits. The SM enhances the BAs resume and helps land those lucrative and career- growing opportunities too. That’s why you should invest in the Scrum Master Certification and start implementing scrum in your personal and work life.
Happy Scrum business analysis to you!

Skills and Qualities Of Business Analyst

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Skills and Qualities Of Business Analyst

The role of a business analyst is super important in an organization. With the help of data, business analysts analyze the problems of a business, and provide solutions for them.
The job of a business analyst is a highly-competitive one. If you are aspiring to be a successful business analyst, technical knowledge alone can’t help you achieve that goal.
In order to successfully implement the knowledge and training, a business analyst needs a few more skills and qualities. These skills can be divided into Hard Skills and Soft Skills.

Hard Skills of a Business Analyst

The term ‘Hard Skills’ is used to denote job-specific skills that are primarily related to the theoretical and practical knowledge of the subject. In case of a business analyst, they can be:
Knowledge of the industry: apart from the bookish knowledge, a business analyst should have a thorough understanding of his industry. The trends of business keep changing rapidly. A business analyst must keep up with the current trends.
Analytical skills: Analysis is the primary function of a business analyst. The analysis requirements can be of various level viz. the business-level, the software level, and the information level.
Collaborating with stakeholders: To successfully function as a business analyst, one might need to frequently collaborate with stakeholders. This is a key step in finding out the requirements of a business, and also discovering the problems (of a business) as well as the reasons behind them. After discovering the requirements, a business analyst should also be able to validate their importance and propose actions accordingly.

Soft Skills of a Business Analyst

Soft skills are those skills that are necessary for functioning well in workplace. They are not specific to any job or field of work, however, your job description is a contributing factor in deciding the must-have soft skills for you. For a business analyst, they are:
Communication skills: Business analysts must have great communication skills. Both verbal and written communication skills are important for them. As they take part in critical meetings regarding the present and future of a business, a business analyst should pay attention to listening, understanding, reflecting, and then conveying their thoughts in a clear and direct way to the team. A business analyst also needs to maintain documentation, plans and analysis reports etc. To present their ideas in front of the board, they also need good presentation skills. These are all parts of written and non-verbal communication.
Problem-solving skills: The core functionality of a business analyst is problem solving. Whatever a business analyst does, it’s some kind of problem-solving or the other. To successfully solve a major problem, a business analyst needs to think out-of-the-box, critically analyze the situation, discover the reasons for the problem, comparing all the possible solutions and coming up with the best one.
Decision-making skills: Another important skill of a business analyst is to take decisions. While working in collaboration with others, conflicts may occur easily. In a confusing situation, taking the best decision for your business is a critical responsibility. A good business analyst should consider every aspect of the problem, talk to the stakeholders if needed, find out about the priorities of the business from the business heads, and then select a plan or a course of action.
Negotiation skills: A business analyst often acts as a bridge between the customers and the developers. That’s why they need excellent persuasion and negotiation skills to manage both the demands of the clients and customers, as well as looking after the needs of the business. Negotiation skills are also necessary while bagging a deal with clients and beat the competitors.
Time management skills: Multi-tasking is a part of the job of a business analyst. That’s why time management skills are very important for them. In order to efficiently manage all the tasks in hand, a business analyst must be able to sort the tasks according to their priorities and stick to the schedule.
Leadership skills: Since business analysts work on a managerial level, leadership skills are also a must for them.
So, these are the most essential skills of a business analyst. If you are looking forward to a successful career in this field, you must learn all of them as soon as possible.

How Do I Switch My Career to a Business Analyst

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Switching careers is never easy and the first recommendation to achieving your goal is to make your action plan after actually doing a SWOT analysis. Let us look at the essential steps involved.
Step-1: Set a goal and a specific time frame
While this may seem simple, place your decisions and goal on the sound basis of research and facts. Evaluate the BA role, its growth prospects, qualifications needed, where you intend to work, certifications, Business analyst course needed and such factual information before doing so.

Business Analyst Role

Primarily, the BA’s role is to provide data analysis and business intelligence while being the buffer between the business in its initiative to improve efficiency and its IT department. Among the many core areas of functioning are:

  • Cost reduction
  • Reporting
  • Monitoring and planning
  • Regulatory requirements
  • Creating new strategic business models
  • Variance analysis and business decision support measures
  • Importing data & understanding KPIs
  • Budgeting, forecasting & financial analysis

If you are already in these roles and are looking to grow into the BA role, here is what you would need to do.

Skills for the Business Analyst Career

Most BAs are graduates with excellent facilitative communication, interpersonal, consultative and oral skills required to understand business needs and stakeholder needs. One needs to think on their feet and be innovative with solutions to recognizing problems in the business structure, engineering requirements, analysis of stakeholders, process modeling and everything in between the IT and business requirements. Understanding the underpinned networks, technology and databases can help in accurate, detail oriented and factual reporting.
You can benefit immensely from boot camps, online resources like free courses and MOOCs of reputed universities like Oxford, Stanford, MIT etc, or do a paid course depending on your time and learning style. Reading books, joining forums and networks and transforming your CV can also help.
Technical skills involved may not specifically need experience in database or programming skills and depend on your job role. Normally, you can expect to use software such as Microsoft PowerPoint, Excel, Access, Google Tableau and Analytics, SQL, visualization and data analysis tools. Presentations are important and knowledge of creating tables, graphs etc. are a plus. If you are a graduate in computer science or data analysis, pursuing your Masters is a good choice for career advancement.
Step-2: Act on your action plan tirelessly
Once the plan of action is in place you will need to get around to doing tasks that will need time, resources, and plenty of determination and effort. Here’s the “Why do it?” question answered.

Salaries and Job Prospects:

According to Indeed, freshers can expect average salaries higher than 17,779/month and without experience. As your experience and capabilities grow the payouts increase. A Senior BA gets an average of 5, 55,792/annum with 1-4 years of experience. Companies like Merck, Fidelity investments, Flipkart and others have recruited BAs.

Demand for jobs:
The BA is assured of ever growing demand as a BLS report in the USA predicts a growth of 14% by the year 2024 for this evolving and much sought after role.

Certifications and courses:
Doing the right course can give you an opportunity to placements, measurable skills and an enhanced resume since skills are the only criteria for the BA role. Organizations like the PMI, IIBA, IQBBA, IREB etc offer certifications that are industrially accepted and valued too.

Conclusion:
Although it may seem like there are only two steps to making a switch from your current role to that of a Business analyst career, reality isn’t that simple. Rerouting to take on new responsibilities requires a lot of focus, dedication and determination. One must plan properly before setting goals and maintain a time frame to research the role, demand for jobs, training institutes, certifications and more. The execution of plans will need resources, money, time and a lot of effort. However, the end result is a plum role of BA where the job is satisfying and earns handsomely. No matter what kind of role you are in currently, your present skills count and can be up-skilled with a Business analyst course.

Also Read: Scope of Career as Business Analyst in India

What Are An Interesting Careers To Explore In Big Data?

Posted on by Imarticus Learning

What Are An Interesting Careers To Explore In Big Data?

Big Data is no longer a future capability but is already in use in a variety of sectors and industries. Some of the uses are as diverse as taxis in Sweden using data to cut back on traffic and emissions to Barcelona building a smart city based on data and farmers worldwide using data to reinvent farms. The benefits of Big Data applications and data-driven strategies have thrown open the doors to a variety of careers which are satisfying, always in demand and pay very well.

Doing a big data course is one of the best options to hone your skills on the current demands of the emerging technologies in Big Data and allied fields like machine learning, artificial intelligence, deep learning, and neural networks among others.

Let us explore the top careers and the requirements to make a career in this lucrative area. Salaries are as reported in Payscale.

  • DATA SCIENTIST: These are the experts who produce meaningful insights and work with Big Data volumes using their technical and analytical skills to clean, parse and prepare data sets from which an analyst can apply algorithms to get business insights. Their salary is in the range of 65,000 to110,000 USD.
  • BIG DATA ENGINEER: These engineers evaluate, build, maintain, develop, and test big data solutions created by solutions architects. Their salaries lie between 100,000 to 165,000 USD.
  • DATA ENGINEER: The engineer is responsible for data architecture and the continuous data flow between applications and servers. Their salary range is 60,0945 to124,635USD.
  • ML- SCIENTIST: They work with adaptive systems and algorithm development and research. They explore Big Data and train the big data course to automatically extract trends and patterns used in demand forecasting and product suggestions. The average ML scientist’s salary is 78,857 to124,597 USD.
  • DEVELOPER-DATA VISUALIZATION: These people are responsible for the development, design, and production of interactive data-visualizations. They are the artists who bring to life reusable graphic/data visualizations. Their technical expertise is valued and the salary range is 108,000 to130,000 USD.
  • SPECIALIST- BUSINESS ANALYTICS: This specialist assists in testing, supports various activities, performs research in business issues, develops cost-effective solutions and develops test scripts. Their salary range is 50,861to 94,209 USD.
  • BI- ENGINEER: These engineers have business intelligence data analysis expertise and set up queries, reporting tools etc while maintaining the data warehouses. Their expertise earns salaries in the range of 96,710 to138,591 USD.
  • SOLUTION ARCHITECT- BI: These architects deal with solutions that aid sensitive timely decisions for businesses. The salary range for this role is 107,000 to162,000 USD.
  • SPECIALIST- BI: These people also are from the BI area and support the framework across the enterprise. The salary range for these is in the range of 77,969 to128,337 USD.
  • ML ENGINEER: This important aspect of ML develops solutions aiding machines to self-learn and autonomously run without human supervision. ML engineer’s draw a salary of 96,710 to138,591 USD.
  • ANALYTICS MANAGER: This manager deals with the design, configuration, support and implementation of analysis tools and solutions from huge transaction volumes. Their salary range is 83,910 to134,943 USD.
  • STATISTICIAN: These people are tasked with gathering, displaying and organizing numerical data used to make predictions and spot trends. The salary range for this role is 57,000 to 80,110 USD.

The skills required:

The basic attributes required for these jobs is:

  • Knowledge of Apache Hadoop, NoSQL, SQL, Spark, and other general-purpose programming languages.
  • Skills honed in a regular big data analytics course.
  • Adept in ML, data mining, quantitative analysis, data visualization and statistical inferences.
  • Personality attributes like being a team player who is adroit in creative and analytical thinking, innovative approaches and creative problem-solving.

The importance of certifications: 

Certifications endorse your skills and validate that you have the knowledge to practically apply your skills. Certifications in the below subjects will stand you in good stead when at interviews and improve your career prospects. Do go in for certifications in

  • Hadoop, SAS
  • Microsoft Excel
  • Python, R, and the Java suite
  • Pandas, MongoDB
  • Apache Spark, Scala, Storm, Cassandra, etc
  • MapReduce, Cloudera, and HBase
  • Pig, Flume, Hive, and Zookeeper.

Parting notes:

It is best to do the big data course at Imarticus Learning as they train you to be career-ready with skills on the latest technologies like the ones mentioned above. Their certification is well-accepted in the industry. So, why wait? Start on your career journey today!