Who would not like to be known as the person ‘who shall fix it all’, ‘the problem solver’? If you are someone who looks at every problem as a challenge only eager to solve it, then the role of a business analyst is ideal for you as the very core of a business analyst’s role is to find solutions, to be a problem solver. Technology evolution, especially in the last couple of decades, has drastically changed the manner in which business issues and challenges are resolved by IT-based solutions. IT intervention is not limited to merely IT management, but its prominence has shifted to that of value creation, by offering technology-based business solutions. Hence a Business Analyst becomes the go-to person within an organisation to provide such solutions. Business Analyst currently is the most valued in almost all domains across industries.
Some advantages of choosing the role of a Business Analyst
Networking, if you are a person who does not like to work in silos, then this is the job for you as it is expected that you collaborate with every stakeholder and business head internally, and customer base and client, on the external front, so basically with the ‘who is who’ of the company on an internal and external front. Not to forget travel becomes a part of the job when you have to liaise with clients at their home front, to understand their processes in their environment.
Multi-Tasking on different fronts, a business analyst usually maintains a bird’s eye view and simultaneously works on several things at the same time. They need to Analyse Requirements, Consider Research Options, Understand Functional and Technical Requirements, be a Team Leader, the Change Agent, Document and the Meetings, and Communicate with the client via Presentations, and at the time do all this in a day! So basically they have to manage all areas of a project with flexibility and be approachable. No wonder they are the most sought-after people in an organisation.
Opens up further Career Opportunity, this role does not restrict you to IT or any specific domain, in fact, it is very versatile, with as less as 3-5 years of experience you can decide how do you want to take this role ahead. Functional Analyst becomes an option if you intend to pursue a specific domain or technology. IT Business Analyst is another option if you where you can position yourself as a mediator between Business and Technology. This role also opens up the Managerial Vertical where with the required exposure and skills one can consider a role in Project Management. Thus a career as a business analyst is highly sought after as it has the flexibility to pursue any role that you desire and achieve the growth that you seek.
Independence and Flexibility, since your role involves liaising with top management, there is minimal micromanagement and a great amount of freedom to bring in responsibility, trust, creativity, in accomplishing tasks.
Every day of a business analyst is different. With more organisations understanding the benefit of a dedicated business analyst position, the job market is set to explode. The role offers great pay packages. With a high sense of achievement and contribution that you get while performing your tasks, it can be said that the business analyst career is close to perfect.
It has the three pillars of financial stability, professional growth, and professional satisfaction. So if you are a fresh graduate and looking at career options, a business analyst’s role should be on your list.
Career in the field of Business Analysis is one of the fastest-growing in the country but like any other profession, excelling in this too requires one to augment top-notch business skills and personal attributes. Possessing innate ability to excel in the field or apt training is quintessential to establish a successful career in this field. Imarticus Learning lists out the essential attributes that professional aspiring to be successful business analysts must possess:
- Communication Skills
Being a business analyst, one is required to interact with users, clients, management and developers. This mere act highly influences a project’s success for the fact that through interaction business analyst clearly communicates the details like project requirements, requested changes and testing results. Hence, fluent language skills and written communication abilities are essential to thrive as a business analyst.
- Technical Skills
A good deal of communication on the part of business analyst is possible only if the individual possesses sound technical skills too. A business analyst would be able to identify business solutions only if he has knowledge of how information technology applications are being utilized, what new possible outcomes can be achieved through current platforms and what the latest technology offers. Other important skills of a technical business analyst include testing software and designing business systems. This knowledge is highly essential to render desired confidence about business as well as technology and ultimately demonstrate a strong technical aptitude.
- Analytical Skills
High level of analytical skills is one such trait that is essential to excel as a business analyst. This skill set helps in properly interpreting customer’s business needs and translating the same into application and operational requirements. Herein one important aspect is to analyze data, documents, user input surveys and workflow to determine which course of action will correct the business problem. Possess a strong hold on these this important skill to fit the role of business analyst perfectly.
- Problem Solving Skills
While the ability to create workable solutions to business problems is not unique to business analysts, it is a necessary skill for performing the job successfully. As with most IT roles, the business analyst’s career may be spent dealing with frequent and random changes. When these professionals are working to developing custom business solutions, nothing is 100% predictable – so finding ways to quickly resolve problems and move toward a project’s successful completion is important in the business analyst’s role.
- Decision-Making Skills
Analysis is one aspect and decision making based upon thorough analysis, another. Owing to this a business analyst should be able to make decisions. As a consultant to management and advisor to developers, the business analyst is called upon for sound judgment on various business related matters. Hence thoroughly assessing a situation, receiving the inputs from the stakeholders and eventually selecting the best course of action is what a business analyst should be well versed in.
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So at long last, you have decided and wanted to take up the most desired confirmation in the Business examination space after much tarrying and thoughts. Most importantly I should praise you on your plans of getting confirmed. That is the best blessing potentially you can give your expert profession.
Uplifting news is that an ever increasing number of experts are taking it up and making it all the more sought after. The underlying trepidation on the new example of CBAP certification exam on BABOK v3 appear to be blurring with this notoriety.
IIBA has likewise as of late declared the dates for the v3 exam comes about after the benchmarking of the pass score is finished.
Out of the considerable number of information sources we have in most recent couple of months, you can take these outline and get ready in like manner:
• The inquiries will be a blend of case and situations, cases will be very long, be set up to peruse long cases
• Situations are short however the choices are the testing since there are no less than two which are near each other
• No retention of data sources, errands and so on required like V2
• There will be computation based inquiries with decimals and so on so be set up to do the counts
• Need great time administration to answer all inquiries
Get ready for the CBAP accreditation exam can be an overwhelming undertaking and here there are few hints to enable you to clear the exam:
Set an Action Plan
Having an activity design is essential, regardless of what exam you’re planning for. Get hold of the investigation materials and settle on how long or week you have to get ready for the exam. Consider on the off chance that you’ve some essential venture running in your office.
Defining an objective and attempting your best to accomplish it can go far in beginning on with the voyage. A 3-month planning time is pretty sufficiently much for CBAP exam. You can likewise enrol for the exam well early as to submit yourself for a broad arrangement.
Gather Your Resources
Assets and study guides are fundamental, so ensure you have them all. BABOK or Business Analysis Body of Knowledge is the Bible of individuals planning for CBAP exam. In any case, it can be a lot for one thing. It’s better in the event that you search for books and aides that give you an unmistakable comprehension of the essentials of business examination in a less demanding way. There are many in the market and search for ones that offer stories and theoretical situations. Read audits before picking one.
BABOK— the Quintessential Guide
Regardless of which control you begin with, you’d need to in the end wind up with BABOK. Get ready for the CBAP exam is fragmented without experiencing BABOK by heart. Make a point to peruse each and every thing in the book to connect all the information you picked up from the various examination materials.
Show Your Knowledge
While remembering the terms given in BABOK is more than a need, having the capacity to apply those ideas is additionally vital with regards to progress. In the CBAP exam, you’ll gone over various situational situations and an unmistakable comprehension of the dialect and use of the six information ranges is basic. You have to adjust your business investigation experience and abilities with the exam inquiries to succeed.
Have a Clear Understanding of the Concepts
Basically looking over parts will accomplish more damage than great to your arrangement. Keeping in mind the end goal to pass, you need a legitimate comprehension of the thoughts and idea and apply them to whatever setting you’re given in the exam lobby. Try not to hustle while giving answers—read and think precisely before endeavouring each inquiry.
Indian Capital Markets have shown remarkable growth in the post-Liberalization era and it remains one of the most resilient globally and poised to be one of the Top destinations for domestic and global businesses to expand and invest in. Raising capital is a strategic priority across India and role of Capital Markets has assumed far greater importance and urgency.
India’s capital markets are currently valued at $140 billion, according to a report by McKinsey & Co. The consulting firm further states that India can unlock a further $100 billion in fresh funding each year for India Inc. if policymakers implement the right policies and fiscal measures to deepen the country’s capital market.
The size of the market can rise even further to $240 billion in a year’s time, but as it stands today, India’s ability to receive funding at scale is moderate at best with shallow pricing efficiency. In comparison, Australia and Japan rank much higher in funding. India needs policies to channel its substantial savings into productive endeavours and accelerate economic growth to potentially lift millions from poverty.
Emerging economies, including India, do not have access to predictable capital market funding at scale and investors lack the financial instruments to channelize long-term savings. This often leads to poor allocation resources pulling down growth prospects. The report suggested that deeper capital markets in emerging Asia could free up a cumulative $800 billion in funding annually, mostly for mid- to large-sized corporations and infrastructure.
The biggest challenge for India is to develop the corporate bond and securitization market, the report further iterates. Emerging market issuers lack options to diversify funding and to match funding with their needs. The absence of a long-dated bond market diminishes corporate borrowers’ flexibility to align funding structure with assets. The listing of government-controlled entities is a step in the right direction as it may lure investors to capital markets. Further, mandating state-controlled entities to tap debt capital for funds instead of going for bank loans is a step in the right direction as well.
Issues in emerging markets face a more volatile and higher cost of capital compared to developed economies. They pay roughly a 120 percentage point higher real cost for debt securities, making it difficult to raise funds for new ventures and to grow existing large companies or conglomerates.
Apart from more prudent fiscal policies and implementation measures by the Government of India, what this essentially is a change management challenge that requires a new mindset. Back in 2015, the US and Indian Governments were in serious talks to discuss potential avenues of technical collaboration between the Ministry of Finance and the US Department of Treasury in developing deeper and more robust Indian capital markets. In April 2017, the capital markets regulator SEBI introduced new products and stricter control measures to deepen the Indian capital markets. For instance, SEBI now allows investors to use e-wallets to buy mutual funds, which would potentially increase inflows into India’s Rs18 trillion MF markets. These are welcome moves indeed!
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Data engineering and data scientist are job titles which might be new to us in recent times, however, these roles have been around for a while.
Traditionally, anyone who would analyse data would be called a Data Analyst, and the person responsible for creating platforms to support the analysis is a Business Developer.
In the world of IT, the data scientist gets more visibility and praise, as they are the ones, extracting vital intelligence from big data and help organisations take critical decisions with regards to their business swiftly. But it is important to note that the data scientist does not work in isolation, they are not capable of generating valuable information independently, and they need the constant support of Data Engineers. The engineers are the ones designing and maintaining software and platforms that operate the big data pipeline. They set the stage and keep it running.
A Data Scientist is someone who is an excellent statistician, with above average software engineering skills. Should be primarily inquisitive, have the skills of data visualisation and storytelling along with programming skills. His tasks would essentially be to identify the question and finding answers through data, finding a correlation between dissimilar data, to be able to tell the findings, hence storytelling ability, and lastly should be hands on with tools like Julia, Python Programming, data visualisation tools like Qlik view or Tableau.
The description of Data Engineers and Data Scientist can be quite obscure, there is an overlap. While these roles still maintain to be distinct data science job roles, they require different skills and experience. Some data scientist can do data engineering, while some data engineers can do data analysis and visualisation as well.
The emergence of big data has opened space for new titles and roles to come into existence. Over the past couple of years’ businesses have applied all means to get individuals who have the skills to turn data into gold.
A lot has changed in the way businesses function, earlier a lot of companies were functioning in the physical world, nowadays most businesses function on the digital platform. When a company is mostly functioning online, there is a huge accumulation of data. Data about who is visiting your website, if they are choosing your competitor’s website as opposed to yours, what could be the reason, you also get data about the statistics of the competitor’s target audience, So the possibility of the data accumulation is too big and very fast. The data are screaming information and is noisy beyond comprehension.
In order to find a way in this data, one needs to sort this in two ways,
Firstly, to create a database to process the data and to store it and the second would be the need of people to comprehend the data and know how to ask a relevant question and research the data in a method that the concerned business can take informed pointers from it. This stored data needs people who know statistics who know how to write code, in order to get insightful information.
Data Scientist and Data Engineers are these people; they are the need of the hour. To know how to process data using various platforms, and more importantly, we need them to be around, These people also know how making sense of the information, how to analyse it. They don’t only plot graphs from data collected from a spreadsheet but also create statistical models that over a period of time affects the business and products with effective ways to increase the revenue.
The data available could be stand but smart and appropriately skilled people are the ones who help find that needle in the haystack.
You cannot achieve tomorrow’s results using yesterday’s methods, and this line is the need to understand and accept the impact of BIG DATA and growing demands of business.
Big data means access to big information, leading to abilities in doing things you could not do before.
Case in point – a small exercise…
Before you read ahead, check the posture you are sitting in, now look around and check the posture of others sitting beside you, observe… what do you see? Someone is slouching. Someone has their legs crossed, elbows resting on the armchair, palms pressed against their chins, a constant moving of the limbs. Not everyone sitting around you has the same posture. What if we put many sensors on the chairs around you to help record and create an index, which is unique to you, which says person X sits in these particular postures during specific intervals of the day?
In addition, say what if this data was sold to car manufacturers as an anti-theft design to help recognise that the person sitting behind the wheel is not the same and say until he keys in a password the car even though entered would not start.
Now imagine what if every single car in the world had this technology, think of the benefits of aggregating this data. Maybe we would be able to predict which postures while driving would lead to an accident say in something as close as the next 7 seconds do, and alert the driver to change position or take a break from driving.
Now my dear reader THAT is the power of BIG DATA. It can help record, collect, understand, predict, and prevent events from a random collection of information.
So if that is so useful where lies the problem? Why is the world not already a better place?
Because there is a gap between opportunity and demand in skilled professionals to help comprehend and present valuable insights into specific relevant trends, big or small from the available data.
Big data is all around us and there is a calling need to preserve all the generated data for the fear of missing something that could be important. Hence, comes the need for big data Analytics, Big data is crucial to do better business, to take accurate decisions and in always being a step ahead of your competitors. Therefore, if you are a professional in the Analytics domain there is a sea of opportunity waiting for you to dive in.
Big data Analytics is Unfathomable and depending on the environment one can choose from
- Prescriptive Analytics
- Descriptive Analytics
- Predictive Analytics
Big Data Analytics market is predicted to surpass $125 billion in between 2015 – 2020, which in turn in some sense means handsome pay brackets for the skilled individual.
- Salary Aspect
To improve the performance of the organisation, most companies have either already implemented or are in the process of implementing Big Data Analytics, as they already have the data at their disposal.
- All Organisations adopting some form of Data Analytics = Growing Market
There is a big gap in skilled professionals who are able to convert the data available. The ability to see small trends from the pool of big information. Which ultimately advances the organisation in the right direction. There are two types of talent deficits. Data consultants – who have the ability to not only, understand but also use the data at hand in the appropriate way and the other is Data Scientists who can perform analytics.
- Skill Deficit
Big data Analytics is not restricted to any specific Domain; it can be and in recent times is being used in Healthcare, Automobiles, Manufacturing and more, creating a massive global demand.
- Global demand across industries
Analytics becomes a competitive resource for organisations, according to certain studies Analytics has already become the most important asset in current times. Because we are emerging from the undeveloped analytics trends to more advanced forms. It is undeniable that Analytics plays a vital role in decision making and taking strategic initiatives for the business.
- Importance of Analytics for Better Decision Making in Organisation
So in deduction to the above, Analytics no matter how advanced is human dependent. These are exciting times for skilled people who can comprehend data and give valuable insights from the business point of view. A trained individual with the right Analytics insight can master an ocean of big data and become an indispensable asset to the organisation becoming a springboard to the business and their career.
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The best possible example of the usage of big data analytics can be found in the legendary fictional works of Sir Arthur Conan Doyle. Sherlock Holmes, as we all know him today through the famous crime detective show, Sherlock is said to be one of the biggest patrons of this concept. The world’s first consulting detective, Holmes once said, “It is a capital mistake to theorize before one has data.” These words uttered during the case of A Study in Scarlet, hold true as data proved to be his timely assistant in solving extremely difficult cases, by helping him come to perfect deductions.
As we accumulate more and more of this data, we feel the need to have optimal processing skills and analytical capabilities in order to process it. India, as a country has been making a lot of growth with many government agencies and private companies, getting on board with the data analytics revolution. Continuing in the same vein, the Comptroller and Auditor General (CAG) has also put together the ‘Big Data Management Policy’ for Indian audit and accounts departments, in order to foster the use of data analytics and ensure the improvement of their functions. Many more efforts are being taken in the same regard, like for instance the Centre for Data Management and Analytics (CDMA) has been inaugurated, in order to synthesize and integrate relevant data for auditing process. The aim here is to exploit data rich environments, on both the state level as well as the central level in order to develop the audit and accounts department.
Data has always helped humans in increasing the level of their decision making skills, in every field of medicine, science, and technology. The recent couple of years saw a great surge in the availability and accessibility of Big Data and its storage options. With big data coming to the fore, it has begun arriving on the scene with alarming velocity, volume, and variety. With so many technological advancements revolving around the accessibility and storage, have led to the opening up of new and empowering possibilities.
On the other hand, there are DISCOMS, which are set up for capturing all the data from the sensors, which are installed in order to analyse the power usage patterns, so as to put together preventive measures for Aggregated Technical and Commercial losses. All the cloud based and predictive analytics solutions given by industries in retail, telecom, and healthcare, have collectively resulted in the rapid growth of the country’s industry and economy. Today as it stands, India has about 600 data analytics firms, in addition to the 100 new start-ups, that have been set up in the year 2015. This clearly reflects on the demand for data scientists in the not so far away future. This is why a number of students have been attracted to the field of data science. As not many generic educational institutes are able to provide the required training, many candidates seek help from professional training institutes like Imarticus Learning, which provide a number of industry endorsed courses in the field of Finance and Data Analytics.
There exist a number of free and accessible Python Machine Learning resources in the market today. While it may be true that anyone can begin their learning process, in a hassle free way but, the amount of variety poses a threat of confusion. Many data aspirants undergo a number of apprehensions like deciding which course to take, how to proceed and most importantly, where exactly to begin.
In order to reduce your apprehensions, we have got here a complete guide to being efficient at understanding and mastering, machine learning with Python. Let’s begin with tackling one of the most important questions, which is ‘Where to Begin?’ While everyone, regardless of the field of study they belong to, faces this question but, it would be agreed upon that to begin somewhere, is the hardest step to take. Couple that with having to make a choice from among the multiple options and you land up confused and staggering.
There are a number of professionals who code but have sufficient working knowledge about computer science. Similarly, if you are looking to get trained in Machine Learning with Python, you don’t need to have a through theoretical knowledge, the practical side more than makes up for it. There exist a number of source libraries, which help with the machine learning aspect, while working with Python. A few of them, those that are known as scientific Python libraries, can be distinguished by the names, nymph (used for N-dimensional array objects), pandas (python data analysis library), matplotlib 2D plotting library) and so on. If you are well aware of the variety of topics of machine learning, which make it easy to work with Python and with the help of professional training courses, it would be a cake walk.
Assuming that the reader is a novice at Machine Learning, Python and any data analysis resources, scientific computing or any other related resource. Let’s begin from the basics, to begin with, you are required to mandatoraly have a certain amount of foundational knowledge about Python, in order to make use of it in Machine Learning. When it comes down to it, your level of experience and comfort in the usage of this data analytics tool, would help you choose the proper starting point. To begin with, you have to first install the Python software, using one with industrial strength implementation for operating services like Linux, Windows is always better.
As most of the work of a Data Scientist revolves around Machine Learning algorithms, it as a whole reflects the field of Data Science. For an aspirant, it is not very important to thoroughly understand kernel methods, as opposed to being well versed with the practical usage of the same. Like they say, practical application of any particular tool, is entirely relative to the theoretical understanding. Machine Learning, in particular, is a concept which very few can learn on their own. This is why most people tend to opt for professional training institutes. Institutes like Imarticus Learning, usually focus on teaching various data analytics tools and machine learning, with a more practical approach coupled with case studies and mentoring from the industry experts.
Data Science as a concept has existed for quite some time, but it’s come into the limelight in very recent times. The whole world is witness to the kind of magic and power, that data analytics generally exudes, as a result of which, it is imperative for every business out there to be able to acknowledge this phenomenon. Regardless of the size, manner, focus area or revenue of a firm, it is essential for it, to understand the dynamics, behind the enormous amount of data, that it generates due to its clients and the maintenance of the same. While there are field where spreadsheets still hold the place of power, but they have long become redundant and obsolete, all because of the emergence of data analytics tools. These data analytics tools are essentially the very important cogs of the proverbial machine, which help data scientist accomplish absolute feats with predictive analytics. So when it comes to the go to tools of data analytics, there ensues an intense debate, so as to which one could happen to be the best or the most efficient aid.
While many believe that SAS programming (mainly due to its time honored presence in the industry and its huge client base), is the tool to go for, lately the younger generation has been differing opinions. Many believe that the best programming language right now is the R Programming language, one of the main reasons cited here, is the fact that R, is an open sourced programming language, which means that it is easily accessible as well as free to be downloaded. Being free of cost, over time, R has generated its own community of users, which includes numerous data scientists, who have all the liberty to develop updated beta versions and to fix the bugs. It has become the hot favorite of all those data analysts and data scientists, working to analyze huge amounts of information and being able to formulate new breakthroughs, in various business fields.
Apart from being a great tool for use in data analytics, R programming comes to be of major use when it comes to business analytics. This programming language basically, makes it very easy for any business to go through its entire data, in the most hassle free manner. It primarily scales all the information, so that numerous parallel processors, are able to work at the same time. As many computers don’t have sufficient memory, to handle and deal with enormous amounts of data, R programming offers ScaleR, which is a part of the application that does the job of trying to re-purpose great amounts, into smaller chunks of information, so that it can be processed on a number of servers, at the very same time. As R allows the users to analyse statistical information in the most sophisticated of manner and in literally a matter of minutes, which most of the other languages cannot really accomplish; this makes R a force to reckon with in the world of business analysis. Rising popularity of R has led to quite a number of people opting to get professional trained in this language, for which majority of them look for institutes offering certification courses like Imarticus Learning.
As the world rapidly becomes data driven today, the most exciting places which are rapidly developing as a result of this are all the startups out there. While data technologies have been around for quite a while now, various factors like the increasing speed of data generation, as well as the ability to store data, have resulted into the emergence of a number of advanced data run startups. Apart from being either involved with data analytics and being data driven, these startups are very unique in terms of their various founding members and the educational backgrounds they belong to, the industry that they work in and the opportunities available therein, the kind of investment and funds they receive or raise and so on. Apart from these deciding factors, there is also the growth factor, which makes for a great importance and good career in big data field in terms of how popular a startup goes on to be.
Here’s a list of four such amazing, Indian start-ups, which would be a dream for any Data Science aspirant, to work with.
Taking the use of data science, to enhance the HR departments of every company out there, this startup was founded in the year 2002. With data science and artificial intelligence, as its core drivers, Edge Networks, in the bid to decrease the cumbersomeness, encountered by a number of job seekers out there, has come up with their product, HIREalchemy. Their solution basically deals with talent acquisition, internal workforce optimization and talent analytics.
Gone are the days, when one would wish for a way to operate any and every electronic device, with the help of a touch screen. Now it is actually possible for anyone to control, any electronic device with a screen, just by their gestures. The best part? An Indian startup, Fluid AI is attempting to create a huge revolution, which would be really gainful for not only the government of India, but also for the Finance, Web and Marketing industries. Imagine how exciting it would be if any screen, could assist you with more efficiency than any human assistance would be able to provide.
Mad Street Den
While we all may joke around about how sometimes, online shopping can be entirely misleading. Especially when you want to buy the kind of dress that you’ve been dreaming of. You find the exact one and order it, but something entirely different is delivered to your place, which is absolutely not what you have been looking for. This is where this start-up’s flagship product, Vue.ai comes into the picture. It relies heavily on the concepts of Machine Learning and Artificial Intelligence and attempts to provide the customers, with exactly what they’ve been looking for by sending targeted emails and the likes.
India is a very large, populous nation and more often than not, a lot of doctors are faced with the herculean task of being able to provide diagnosis, as well as treatment very promptly. This is where this start up comes into the picture. It is being devised to assist various medical practitioners, in rapid diagnosis, with the help of Image Processing, Classification with AI and Machine Learning at its core.
These amazing startups make it seem like a dream, for any Data Scientist to work in the Indian Data Industry. With various institutes like Imarticus Learning, offering specialization courses in various data analytics tools like R, SAS and Hadoop, achieving the dream is very possible today.