Analytics - Finance, Tech & Analytics Career Resources

20 Latest Data Science Jobs For Freshers

Posted on October 26, 2020December 5, 2023 by Imarticus Learning

Data scientists are one of the most sorted after job profiles in recent times. As per the latest report, there are approximately 1 lakh openings for data scientists, analysts or AI skilled professionals. These are also good opportunities for freshers who do not have any experience in this arena.

The best way to land a good placement is to find out the prospects of such profiles and which industries or fields that are looking for such roles. Here are 20 of the latest data analysts, scientists, BFSI, Artificial Intelligence or related job openings for freshers.

Data Scientist- 11 at Accenture in Bangalore. The job is related to the medical field, handling biotech, pharmaceuticals and healthcare as the functional areas.
Associate Data Scientist at UST Global in Thiruvananthapuram- The role requires the integration of the delivery groups to the data management procedure.
Fund Data Research Analyst, Morningstar India In Mumbai for the role of Managed Investment Data related to finance.
Computer Vision & Deep Learning Engineer at SynergyLabs in Gurgaon expects you to work with Python or C++ for deep learning models and its analysis.
Junior Data Analyst at Cognizant in Coimbatore for the role of Analytics and Business Intelligence having skills in coding and Pharmacovigilance & Safety Ops.
AI/ML- Developer at Siemens in Bangalore is looking for graduates having Data Science qualification for developing applications that are prototypes for AI and ML.
Data Associates at Amazon in Hyderabad for Alexa Data Services organization and working with Amazon Machine Learning Science to improve the performance of Alexa.
Content Risk Specialist at Amazon in Bangalore for content evaluation and record management for quality testing.
AI Engineer at huddl.ai in Bangalore- The role requires you to be responsible for the delivery of a collaborative solution for unstructured data using coding, testing and deploying machine learning systems.
Atmospheric Science Specialist at Genesis Ray Energy in Gurgaon is looking for professionals having expertise in machine learning and data science techniques to work with weather prediction models.
These are just a few ideas on what to expect as a data scientist or data analyst. It shows that there is a wider scope in this field and that numerous business fields require the skills of a data scientist in many forms.
Here are a few more opportunities for freshers in the data science field. These roles also have a similar job description and more or less the same skills requirements.
Data Scientist at Arya.ai in Mumbai
Jr Data Scientist at NextGen Invent Corporation, Delhi
Data Scientist, I at iXplore technology in Bangalore
Artificial Intelligence Developer at 1Tab in Noida
Data Scientist at PayPal in Bangalore
Associate Data Scientist at PayPal, Bangalore
Data Science at Accenture, Telangana
Data Scientist- BFSI at Tata Consultancy Services, Bangalore
Decision Scientist I at Flipkart, Bangalore
Data Scientist- Operations Research at Grofers, Bangalore

As for the salary, freshers can earn anywhere between 1.2- 3.4L depending upon their qualifications, skills, and performance in their respective roles.

How to Become a Data Scientist?
Now that you have seen the prospects and opportunities of a data scientist, the first step is to find the most suitable data science course based on the job descriptions posted on various platforms. Find out what the companies are looking for and enrol for the best course or certification.

The most important point to remember is that any degree can help you become a data scientist. You just need to find out the best course that can help you be the one. It would also help to find the trainers who provide placement assistance by arranging for an interview to make your job hunting easier.

What Are The Benefits Of Doing Data Science Course
Why Is Data Science A Good Career In 2021
Why It is Right Time To Pursue A Career In AI, ML & Data Science

Why is Agile Training Important?

Posted on October 23, 2020 by Imarticus Learning

The innovations and developments in various sectors are increasing rapidly. The sectors themselves are becoming more dynamic. This trend doesn’t seem to subside and to stay competitive and efficient, industries and organizations are moving towards agile methodology and agile project management. Not only software industries but other sectors are also following different steps to implement agile. Therefore, agile training is important if you want to understand how agile works.

What is Agile?

Previous standard project methodologies like waterfall used to be static models where the product working model is revealed late during the life cycle. Unlike previous project management methodologies, Agile is result-focused, dynamic, and looks for continuous iteration. The agile methodology looks for adaptive planning, short delivery times, planning, and flexibility. Agile eases the process of collaboration and there is a continuous feedback loop that makes the project development very dynamic and efficient. To achieve this efficiency, agile methodology follows a specific set of processes.

How does Agile work?

Agile stresses on placing at most importance on delivering work projects incrementally and iteratively with a constant presence of stakeholders end to end. To achieve this, there are processes such as scrum, sprint, Kanban, etc.
Client/Company/Employer following agile follow a certain procedure:

Feature/List Creation
Requirement of features
Estimation of the time taken for completion of each task or feature
Prioritization
Execution
Updating/Iteration of the tasks

Sprint: A sprint is a set period where we need to meet a set goal. The sprint follows the above procedure. These sprints gets reiterative till the product becomes satisfactory and feature-rich. The sprint system gives developers the power to decide the tasks in that sprint

Scrum: Scrum is the structured process of organizing a team to reach a common goal. Scrum consists of daily meetings and in these meetings, they discuss and sort out various steps like Backlog, how long a task will take, what is to be completed.

Benefits of Going Agile:

Going agile gives companies leverage to become more efficient. Some of the benefits being:

Higher productivity: Agile is highly collaborative and due to stringent deadlines and daily check-up, the productivity increases.
Better quality: Due to its iterative nature, the quality maintained is higher.
Cost savings: As the stakeholders are present from the get-go, there will be no last-minute escalations which help in cost savings
Stakeholders satisfaction: Due to their constant presence and feedback, there will never be any parity between expected results and executed results.
Faster time to market: The minimum viable product can be delivered in a short period than previous project management methodologies

Company adaptation:

Agile is being rapidly adopted by many renowned companies
Nearly 71% of companies already use Agile methodology
98% of companies are happy with the adoption of Agile
Availability of various software to manage agile is also a reason for the high adaption rate and agile is a norm
The Agile adoption success rate is 42%, while the Waterfall success rate is 26%.

Importance of Agile Training:

Agile training has become important due to the dynamic movement of the sector. Stakeholders want more hands-on experience with their project and choosing agile has become the norm and an ideal scenario for the majority of the companies. Agile training is essential as these companies prefer an employee/executive who is familiar with the process and who can jump into the project development.

Conclusion:
Training in Agile methodologies gives the employee an upper hand during the selection process/interviews. Agile improves the job scope and also increases the number of opportunities available for an employee. Agile training and certification will give a great boost to the candidate.

Also Read: Who Can Do Agile Certification

Secure Your Finance & Analytics Careers With Imarticus!

Posted on October 21, 2020April 1, 2024 by Imarticus Learning

With the growing commercial and technological advancements in the global markets today, Finance and Analytics are quickly becoming one of the most lucrative careers in the business world. Finance & Analytics play a major role in data evaluation for businesses to streamline decision-making processes.

They mainly inform the investment decisions of the companies by researching the microeconomic and macroeconomic situations with the organization’s principles. The professionals in these fields also prepare financial models that project future economic conditions.

Many businesses also hire them to evaluate the efficiency of their marketing techniques in comparison to the cost using numerical data. They also work in franchise-based businesses to track the individual franchise or a group and evaluate their positive and negative points to speculate the growth of the business.

Importance of Finance & Analytics

In this competitive world, businesses today need on-time data to formulate decisions for business. Every company needs good financial and analytics planning to utilize its resources in the best way possible.

The changing needs of businesses and the emergence of new models are making it crucial for companies to have sound Finance and Analytics professionals that help them improve their decision-making

Shape the business goals and plans for optimal performance. The Finance courses and Data Science Course with Placement help businesses to run efficiently and attain their aims fast.

Scope of Finance & Analytics

The careers in these fields are highly coved in the business industry with a good pay scale. The professionals in these fields have ample job opportunities in sectors like banks, pension, insurance companies, mutual funds, and securities firms, etc. Since they assist people in their financial decisions and investments, they can also open their own offices and work as self-employed.

They can also do accounts, auditing, taxes, and prepare financial statements. They can also specialize in other segments like Cost accountancy. The work scope of Finance and Analytics professionals also includes tasks like account management, secretarial work, share valuation, etc.

Job Opportunities

The wide scope of Finance & Analytics allows professionals to find employment in a range of sectors. They can find job roles under the following titles:

Financial Analyst
Chartered Account Trainee
Analyst – Back Office
Accounts Trainee
Assistant Consultant – Business Analyst
Junior Financial Analyst
Management Trainee – Finance
Research Analyst – Option Strategist

The pay range in these roles is also good. The average pay of a Financial Analyst in India is around INR 40,000. With experience, this number multiplies manifold.

Educational Requirements

To build a substantial career in these fields, one needs to have in-depth knowledge along with a good practical skill-set.

For this, students can join vocational programs in Finance and Analytics from reputed institutions. Imarticus is one such renowned organization that is offering courses in these subjects to train students and make them job-ready for the business world. By learning these courses students get:

Guaranteed job interviews
Comprehensive, industry-approved curriculums
Hands-on, experiential learning with cutting-edge technology
Training by industry experts and veterans
Extensive career support and assistance
Certifications accredited by world-class organizations
… And so much more!

Learning with Imarticus

Imarticus Learning is organizing the ‘Great Indian Futuristic Talent Drive’ offering good discounts on its various courses for the festive season from 21st October – 27th October 2020. You can avail of the following discounts by registering in the drive:

Fee Waiver on PG Classroom Programs – Up to 25% off

Fee Waiver on Online ProDegrees – Flat 20%

Fee Waiver on Classroom CIBOP & ProDegrees – Flat 15%

With the online learning mode of Imarticus, you get the facility to learn at home.

Thus, keeping safe during the pandemic and productively using your spare time to upskill yourself for an excellent career.

What’s it Like to Work in Data Analytics as a Graduate?

Posted on October 20, 2020October 21, 2020 by Imarticus Learning

Data Analytics has emerged as a new giant in the business space. With increasing automation, data analytics has found its space and is evolving and transforming how businesses operate. This evolution has created a new market and also anew area where people can find jobs. Becoming a data analytics professional is a challenging task. You need a major upskill to become a decent data analytics professional. A data analytics course will give you the same major insights that are required if you aspire to make a career in the field of data analytics.

Work of a Graduate Who Gets into Data Analytics

Graduates who join the field of data analytics are known to be highly skilled. They have an analytical bent of mind. Also, they are equipped with high order thinking skills. Graduates today have access to a plethora of activities in the field of data analytics. Also, you don’t need to be born with the required skillset. You can build the skillset in stipulated time by taking a Data Analytics course. Some of the work done by graduates in the field of data analytics are:

They are responsible for maintaining huge data sets. They also design different data systems and develop databases from different data management systems. They also manage datasets and databases with the help of building algorithms and also by some basic coding which comes in handy for effective management of data. A graduate must have a basic understanding of programming languages like R, Python, etc. You can also take up a data analytics course for this purpose.
Dat mining is also a very important part of their jobs. They look for verified data sources and then extract data from those sources. Also, the data extracted is quite raw and it has to be filtered and organised. This activity is also performed by graduate analysts. This data sorting provides the basis of any activity that will be carried on further with the help of this data. Also, a standard format has to be followed as the data has to be made readable.
Graduate analysts also make use of different statistical tools for data interpretation and analysis. Also, they are held responsible for trend analysis and making other interpretations which will be useful for business. These interpretations are converted into business decisions. A graduate analyst needs to be aware of tools like regression, data interpretation, dispersion, etc.
They are also responsible for making reports based on the data extracted. These reports have different purposes. Company leaders access these reports to understand how the company is functioning. These reports can effectively communicate different kinds of patterns and trends which are of great importance to the company.
Graduate analysts also work together with programmers to develop different processes that can contribute to the entire data management system more effective and efficient. They help in improving the systems around which the entire system works. These analysts use programmes developed by the programmers for their daily processes and work. They know how a particular programme can be made better

These graduate analysts also interact with a lot of different stakeholders. Therefore, they need to work with precision. Also, the groundwork has to be made concrete so that these data sets and documents can be used effectively for improving the business processes. Graduates are increasingly taking up jobs in the field of data analytics and are growing at a high pace. This makes it a very desirable field of work for graduates.

What Are the Benefits of Doing Data Science Course?

Posted on October 20, 2020December 5, 2023 by Imarticus Learning

What Are the Benefits of Doing a Data Science Course?

A data scientist is a professional having relevant expertise in the field of technology to use data for the betterment of the business. With plenty of information and data from various fields, the scope for a data scientist has no limits. But first, one needs to enroll in a Data Science Course to gain and polish knowledge in the field.
Data Science training is a path-breaking career opportunity with a multitude of scope. It provides a progressive career as well as a glorious salary. Most importantly, it will never be a monotonous job but a very exciting and engaging one.

What are the benefits of data training?

High demand
A data scientist is an in-demand job opportunity and whoever has successfully completed the course has a better chance of landing a job.
Since data is the ruling factor for all businesses, all need someone who can handle them properly. Data Science course can just ensure this eligibility criterion.
Moreover, a data scientist is a key role player who can determine and define the company’s success.
Plenty of opportunities
Every business is looking at the big fat data source for their success. The data involves anything from the most productive date to the single product that the public is more interested in. Determining what is appealing to the public is essential for decision making. This demand makes way for more opportunities for data scientists. Anyone who is well versed in Data Science and knows its nuances can easily spot the key areas and make the necessary changes in the plan.
Better remuneration
Owing to the high demand and opportunity for doing something larger, a data scientist is likely to get some handsome remuneration. With proper training comes certain qualities such as analytical powers, polish the leadership qualities, thinking smart rather than harder. All of these are necessary attributes for a data scientist to emerge from the vast sea of data sources and tools.
Once you have established your skills and proven your worth, it would only be a matter of time that converts into better payment.
Versatile field
The very demand for a data scientist is high because Data Science is applicable in almost every field of life. From ordering the morning milk through smartphones to managing employees’ data by HR, every field is flowing with data and information.
All these fields require someone to deal with them in the most appropriate manner that brings more business and opportunities. This versatility in the field is available for a very few profiles and a data scientist is sitting right at the top.
Having some proper training in this arena opens up new opportunities and adaptability to the jobs.
A smart move for personal growth
Data analysis is a wonderful opportunity for anyone who is interested in data. The Data Science Course ensures that they follow the right path. While the training helps sharpen their skills it is a smart move towards personal growth as well.
As mentioned, it helps improve various qualities within that would surely reward in the near future. In addition, it is also an excellent opportunity to brush up on communication skills as well.

Conclusion
Data-driven analysis requires elaborate and specific technological knowledge. At the same time, one cannot master analytics in a single go. It needs regular updates and such data analysis courses are definitely worth the time and effort.
In short, even if the data scientist training has its benefits, one must not stop at a single course and should be willing to look for new and updated knowledge, from time to time.

Related Articles:

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

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

What are the Different Types of Business Management?

Posted on October 20, 2020 by Imarticus Learning

Business management is a discipline that is devoted to analyzing, organizing, and strategizing various business operations. It includes plenty of things like money, machines, production, innovation, and marketing, etc. In a corporate environment, business management includes directing or leading the people and controlling or managing the organization.

There are a lot of branches of business management that serve different purposes. They are divided based on their core characteristics. However, some of their functions can overlap.

Types of business management

There are eight types of business management in total. These are:

Financial management
Human resource management
Production management
Marketing management
Strategic management
Service management
IT management
Operations management
Let us discuss them in detail.

Financial Management: Financial management is one of the most important types of business management. It deals with finding the balance between profit and loss to understand the growth of the business. It involves coordination between accounting, banking, investing, etc. A business management course in financial management leads to jobs like finance officer, financial analyst, financial advisor, etc.
Human Resource Management: Human resource management focuses on recruitment, management, and direction of people working in an organization. The main duties of human resource management are compensation, benefits, safety, and wellness implementation in the organization. Earlier human resource management was focused only on personnel administration. However, these days it also includes strategic utilization of employees and implementation of employee benefit programs to add value.
Production Management: Production management involves decision-making about the manufacturing of products and services. Methods, Machines, Materials, and Money are the four M’s that production management revolves around. A business management course in production management ensures good scope in this field. To ensure that production is at the optimal level, production management focuses on inventory control and employee training. Research and development processes for the growth of the organization also come under production management.
Marketing Management: Marketing management deals with the managing of marketing resources and activities of the organization. Strategy, brand management, pricing, etc. are all part of this branch of business management. Effective marketing management ensures maximum ROI for the business. The major areas of marketing management are competitor analysis, company analysis, collaborator analysis, and customer analysis. The scope of marketing management depends on the size of the business.
Strategic Management: Strategic management involves the execution of strategic thinking in major activities of the organization. Many other branches of business management such as finance, operations, and marketing use strategic management for their optimal performance. It helps to see the ‘bigger picture’ of the organization.
Service Management: Service management roles differ from organization to organization. Generally, it involves automated systems and skilled laborers for the effective execution of a task. It helps the business understand its products and services from the consumers’ perspective. A business management course in this branch leads to job roles like mechanical maintenance manager, service manager, Project leader – service management, etc.
IT Management: IT management is the management of the technological resources of an organization. IT management modify the technology of business to align it with the strategies and goals of the business. Service, IT configuration, and financial management are the key elements of IT management. They implement and administer the information and communication technologies of the business.
Operations Management: Operations management’s role is to ensure that all the operations in every department of the organization are running smoothly. It involves dealing with different processes, strategies, and departments. It makes sure that the development and utilization of resources are happening properly within the organization. The functions of operation management can vary depending on the business and industry.

How Freshers Can Get Real-World Job Experience In Data Science

Posted on October 12, 2020March 26, 2024 by Imarticus Learning

Introduction

For most freshers, landing a Data Science job seems like a chicken-or-egg situation. You need to have hands-on work experience to get selected for such a job, but how do you get any work experience without first being hired?

By now, you must have heard, read or seen a lot about the scope for immense growth that a Data Science career can offer. However, for many aspiring Data Scientists, the reality appears to be hard-hitting.

The career potential of a Data Scientist is undoubtedly very rewarding once an individual gets the job, but getting the job without prior work experience is the main obstacle they face. Below, we examine some practical solutions to this dilemma:

Work on personal Data Science projects

This is an interesting and highly practical way to gain real-life Data Science experience. Once you finish a project, you can showcase your work on a platform like GitHub. Focus on small projects, and try to demonstrate important Data Science skills in your efforts.

The advantages of working on your own project are that you gain hands-on experience in generating ideas, collecting data, cleaning data, analysing data and building predictive models.

Therefore, you gain a comprehensive understanding of the entire process. As far as possible, try to script clean codes and develop clear visualizations that potential stakeholders can find easier to follow.

Do not attempt to display too many skills at once, as you might end up unnecessarily complicating matters for your audience. Simple and small projects will illuminate the core skills you wish to draw attention to. For example, consider obtaining a complicated datasheet and cleaning it up. This simple project will demonstrate your prowess in:

Scoping a data project and formulating a suitable plan
Gathering data using different collection methods
Contemplating different data cleaning methods and choosing the most suitable one
Handling different data formats such as XML, CSV and JSON

Contribute to open-source projects

The best way to enhance your coding skills and get hands-on Data Science experience is to join an open-source community. Providing solutions to projects that are already in progress will help you deal with real-world problems, while giving you a taste of what working in a Data Science team would be like.

As a member of an open-source community, you need to constantly communicate with the other stakeholders when making your contributions. Open-source projects are an excellent way to access Data Science libraries, such as NumPy, Pandas, Scikit-learn, and more. Above all else, being a part of these communities will help you build a professional network with relevant people in the Data industry, and also significantly add to your existing knowledge.

Make tutorial / educational content

If you have confidence in your Data Science skills and knowledge, you can try authoring a Data Science blog feed, or creating tutorial videos that explain the core concepts of Data Science. These are excellent ways to highlight your abilities to prospective employers.

In-person meetups

After you complete a Data Science course, in-person meetups can present great opportunities for face-to-face interactions with industry leaders and representatives. Meetups are essentially corporate events being held in your city, such as business conferences, presentations, seminars, expos or coding competitions.

These events are excellent venues for networking with like-minded professionals who work for a range of different organizations. A simple Google search with keywords like Data Science meetups, along with the name of your city, will generate information about ongoing or upcoming events near you.

Volunteer for a good cause

Many non-profit organizations need Data Science professionals to volunteer for them. This is a good way to give back to society, while at the same time, you could get to work alongside experienced Data Scientists who can guide you and offer valuable career advice.

The tasks you perform can be showcased in your resume, and will be considered as valid work experience. Poverty, Environmental Protection, Equal Education, Public Health and Human Rights are some of the non-profit areas that you can contribute to.

Conclusion

The career scope for a Data Scientist is tremendous, but it often proves difficult to get a Data Science job without a certain amount of relevant work experience. The key is to show recruiters that you possess the requisite expertise and skills to do justice to the job if you are given the opportunity, and the steps listed above will go a long way towards accomplishing that.

How Do I Start Learning Deep Learning?

Posted on October 7, 2020September 20, 2021 by Imarticus Learning

Inspired by the human brain, the artificial neural networks in deep learning helps to solve complex problems using a diverse range of unstructured data set. Deep learning is a subset of machine learning that uses complex algorithms to learn with time by leveraging massive data sets. Deep Learning is used frequently by a lot of industries to automate processes and is among the most in-demand new-age technologies in the contemporary. Some of the most reputed organizations like Google, IBM, Apple, Microsoft, Intel, etc. use deep learning to make their services better. Let us see how to get started with deep learning.

Familiarise Yourself with the Prerequisites

One should make sure he/she knows the prerequisites needed for understanding the deep learning technology. This will help in understanding the neural networks better. You should know about mathematical topics like statistics, calculus, probability, numerical optimisation, etc. to operate on neural networks.

You should also be familiar with the low-level & high-level programming that has libraries for machine learning. Programming is a must-have skill for developing algorithms in deep learning. Languages like Python, Java, C, C++, etc. are used a lot in developing machine learning models.

Learn from Online Sources

You can learn from Deep Learning Courses offered via prominent providers. One can also read articles, blogs, available on deep learning by experts on the internet. One can also understand the deep learning concepts via YouTube videos. The online courses will be of great help as you can get to know about deep learning fundamentals without even going to an institution.
You can pace-up your studies for learning the fundamentals of machine learning & artificial intelligence and then you can take your time as you go deeper into the subject matter of deep neural networks. One can also read various journals on deep learning to understand the new methods & tools in this field and keep themselves updated with the latest in this domain.

Understanding Deep Learning Fundamentals

Once you have acquired the prerequisites for deep learning, dive into the fundamentals of deep learning like Recurrent Neural Networks (RNNs) which can lp to remember all the previous inputs and is used for time series prediction & other chores.

You will also have to know about Natural Language Processing (NLP) where the human language is made more intelligent for machines to perform dedicated tasks. You can also search for courses on the internet that have topics like reinforcement learning, deep learning frameworks, etc. in its course overview. Make sure that you know how to build artificial neural networks from scratch. You will be in heavy demand by the firms if you are skilled in deep learning because of the need of automating processes.

Practical Deep Learning

You can try your hands on the most popular Deep Learning software(s) which are used by firms/industries like Neural Designer, H2O.ai, Microsoft Cognitive Toolkit, Apache SINGA, Caffe, etc. You can work on example data set and can try to design your neural network. Practical learning will make you grasp things better and you will also specialise yourself in building neural networks.

A lot of online courses provide you with industry-oriented learning of deep learning with practical activities. You should be familiar with the tools and applications used in the deep learning industry. You can read case studies on different deep learning problems and can try to find solutions to real-world problems. You can work on various projects available on the internet on deep learning which will hone your skills.

Conclusion
Starting from knowing the prerequisites to building your neural network, you can get started in deep learning easily. If you are good at programming and mathematical skills, then it will take even less time to be skilled in deep learning. A systematic approach towards learning deep learning is offered by many Deep Learning Courses available on the internet. Start learning now!

What is Data Analyst Certification?

Posted on October 7, 2020January 30, 2021 by Imarticus Learning

A data analyst certification is a short-term course that makes you eligible for the entry-level job as a data analyst. The responsibility of an analyst is to find the relevant data for a business to process, analyze, and design it to the best effect for better business prospects.

Finding out the latest trends in any business helps with its growth and attracting more customers or clients. It is the data analyst who processes such data to find the best solution for the ideal growth of the business.

The course

A data analyst certification course includes the understanding of the analyzing tools, certain programming languages to use the data properly, and statistical awareness to compile the data and results to come up with a workable plan.

Most of the certification courses offer real time business experience in collaboration with a specific business or company. It helps the student to have actual experience in the field and what to expect from the job.

Some courses also help with the placement or provide interview opportunities.

Eligibility for the certification

Although knowledge in computer science would be an added advantage, most of the data scientist courses are open for graduates in any field. The most common eligibility criteria include a degree in Mathematics, Computer Science, Statistics, Economics, etc.

Having prior knowledge in programming languages, SQL database, data warehouses, Advanced MS Excel, etc would be an added advantage. Knowledge in these areas would help develop the necessary skills for an analyst to polish and develop the expertise.

The role of an analyst

An analyst is someone who handles the analysis part. Nowadays, almost all businesses utilize the huge bank of data provided by their customers to their best opportunities. In addition to this, there are also various sales and statistical data which could also be an ideal opportunity to grow the business.

Imagine the data to be a thousand-piece puzzle board mixed with other irrelevant puzzle pieces.
An analyst must be able to spot the relevant pieces, categorize them, and analyze it to find the right position to fit into, to make up the whole board complete.

In a similar manner, the analyst needs to find the relevant data, process it properly using the analytics tools, and design it into a workable format using the various programming tools and statistics.

What is expected?

Data analysis in a constantly growing and demanding profession. A data analyst is expected to have certain skills to make the job more efficient. These skills are not confined to academic levels.

A creative mind to interpret the data and a good analytical mind are highly relevant for the analysis. An analyst must have an analytical mind and be creative to use the facts, figures, and specifications to design the plan and execute it well.

As an analyst, you will be expected to predict the change in the business market and find out what the clients need or expectations from the business.

An analyst will need to go understand the goal of the business, go through the data to select the most relevant information. Then, this information is utilized to devise a plan to promote the business and attract more clients.

Enrolling into a quality data analyst certification course is only the first step into the bigger reality called the data analytical world. As mentioned, finding out the latest trend is the key to better prospects and more often this key might be well hidden behind the vast database. An efficient analyst should be able to spot such openings to make way for the inevitable.

Also Read: Will Doing Big Data Analytics Courses Help To Make Mid Career Jump

What is Change Management Tools and Techniques?

Posted on October 6, 2020December 5, 2023 by Imarticus Learning

Change is the only constant, not only in life but also in business. Just the way we adapt to situations in our personal lives, we also need to adapt to changes at work. Thus, a change management course helps a business apply a strategic approach and deal with things that alter. It includes using tools, skills, and resources to drive success.
The best example of change is the coronavirus outbreak in 2020. It forced most businesses to cope up with the current market scenario. The companies that have managed to survive and are still struggling had to adapt to ‘the normal.’ However, many have had to shut down not only because of failing to adapt to changes but also for losing relevancy during trying times.

Change Management Tools and Techniques

To incorporate the change management course, you need tools for your business. Here are the primary techniques that most companies need:

Flowcharting: Flowcharting a basic formula to bring people on board to understand where the company stands and how it is likely to proceed. The best way to go about this is by asking all the managers to give individual options and see how they perceive. It will bring forward conflicting views that can be debatable and concluded upon.
Once you implement a change, you can add it to the flowchart so that every member can keep up with it. The strategy not only helps create the perfect flowchart but also allows everyone to contribute and feel important.
Data collection: Collecting data on facts on how well the company has evolved and where it currently stands is crucial. The process records risks, competition, opportunities, and helps change management in a constructive way. It also reduces decision-making time and avoids unnecessary debates without facts.
Correct data helps create a metric design, which is easy to understand. The process also includes cycle time, range, and total flow of units through the timespan. The results help identify errors and units that need rework.
Force Field Analysis: Psychologist Kurt Lewin developed Force Field Analysis. His theory explains that success is attainable when driving forces are strengthened and resisting forced are weakened.
Inhibitors of change are usually resistance from the members of a business. However, if members can accept change and focus on its benefits, there are more chances of success. The hierarchy needs to help their subordinates to deal with changes and reduce resistance.
Culture mapping: Every business has its own set of concepts, values, practices, and norms. Some typical ones include respect for authority in terms of decision-making and reward system based on performance.
People responsible for change management in a business must be well-versed with the organizational culture; only then can they apply appropriate improvement practices.
One of the most difficult things to change is the attitude of continuing things how it has always been. Thus, the first thing to target is existing paradigms and then move to a newer change management course.
Plan: Having a project plan is the most obvious, but that is also what keeps us on track. A proper plan that everyone follows works like a framework. It helps people understand where there can be flexible and where there needs to be a boundary.

Most times, people working in several business departments need to adapt to changes simultaneously. Thus, it is crucial to utilize the management tactics and have a straightforward plan to propose new alterations.
A sound business plan helps people know their roles and how to manage their deadlines. You need to keep your company agile through the challenges and cope up with changes positively.

Also Read: What are the types of change management

Category: Analytics