Category: Analytics

What is the job of a data engineer? How is it different from the role of a data analyst? What does a data scientist do? Confused? Let us put all the different aspect of data analytics into different buckets and make it all more manageable for you.
If you are looking to migrate to data analytics from any other branch (technical and non-technical), then read this article till the end to comprehend the different choices available for you. Please go through this article even if you belong to the field and are looking for options to upgrade your career and earn some better pay from the area itself. The field of data analytics is a continually changing one, and the roles mentioned here are defined loosely.

There are four significant roles under data analyst responsibilities –

Data Engineer

A data engineer is the one who designs the platform and the structure which gathers and stores all the data from the users such as what item they are buying from an online store and what are the contents of their cart currently as well as on their list. Data engineers ensure that all the data are stored efficiently and are easily retrievable.

Data engineers are adept at working with a range of sources and framing ETL queries to collect data from them quickly. They then organise all the data in databases for the companies and individuals or others to use it from there.
You will need to acquire knowledge of various languages such as Java, Python, C++, SQL, Hadoop, Spark, Ruby, etc. on top of data analytics certification. It should be noted however that there is no need to learn all these languages as the requirement varies from company-to-company.
Being a data engineer provides you with the rare opportunity to work as both a software engineer and a data analyst.

Data Analyst

Data analytics role expects you to prepare insights from the available data which directly impacts decisions in businesses. There is direct involvement of data analysts in everyday business activities. A data analyst or business analyst is expected to perform a significant amount of ad hoc analysis every day. For instance, data analysts help an e-commerce’s marketing team to identify the customer segments for the marketing or the ideal time to market any product or the reasons of the failure of the marketing campaign and how to avoid the mistakes in future. A good understanding of business, statistics and data manipulation is thus required in a data analyst.
The languages and tools which are required to be known by a data analyst include SQL, R, Excel and Tableau for some cases.

Data Visualizer

Every kind of company or organisation in today’s time possess a data visualizer or a business intelligence professional who is/are responsible for creating and presenting weekly insights and chart boards informing the management about the various metrics. The metrics may include the weekly sales of products manufactured by the company, the average time required for the delivery, or the total number of cancellations of orders and the reason for them.

Data Scientist

A data scientist is a person who utilises the data in possession of the organisation to design business-oriented learning models and types of machinery.

For instance, data scientists go through all the available data of the company and look at the buying patterns of the consumers, identify the favourite items and more frequent users. Then they design algorithms based on that to automatically recommend the more popular products to frequent buyers with their navigation histories, purchasing histories or other similar parameters.

Related Article:

• What is Data Analysis and Who Are Data Analysts?
• What is The Difference Between Data Analysis and Data Science?
• Data Analytics Trends in 2018

There is a lot of ambiguity in recent times over the safety of the fixed deposits, which happens to be the lifeline of the middle class. It is due to the new bill introduced by the government in the winter session called the Financial Resolution and Deposit Insurance Bill (FRDI), this bill, if passed will come into effect in the current year 2018.

The anticipation of this bill has resulted in a wave of anxiety, especially amongst people with heavy fixed deposits. FRDI is the new institutional framework designed to deal with bankruptcies in banks.

Let us read on to understand the clauses and impact of the FRDI bill on the banks and depositors.

What is FRDI Bill?

To quickly understand, this bill when commissioned will help to establish a Resolution Corporation, which will be responsible for monitoring the banks and financial firms, by suggesting corrective action. Under this process, the resolution corporation has the right to implement the ‘Bail-in’ process. Under which the bank or the firm’s own fixed deposits will be used to recover from the financial problems faced by them.

Having said this, it is only fair that the corporation provides insurance over the deposit, up to a certain limit in an event of bankruptcy.

It is this bail-in feature of the FRDI bill that is causing the stir amongst people who are criticizing the clause. Mainly because it is the depositor’s money that can be used by the drowning financial institution to stay afloat. In their defence, this is not a very common scenario.

At the moment, the good news is that the Deposit Insurance and Credit Guarantee Corporation (DICGC) is eligible to protect each depositor of the bank for up to a limit of one Lakh. Any amount above that does not cover the guarantee.

It is interesting to note that the resolution corporation will categorize financial firms under 5 categories, Low, Moderate, Material, Imminent and Critical, and will take over the firms which fall under the ‘Critical; category to resolve its issue in a year, extensions might be requested under certain requirements.

Who will get impacted by this bill?

Prima facie it does look like the investor who does not qualify under the insurance clause, the ones who have parked their funds for security purposes with the banks and financial firms will get impacted the most. The current bill supports the banks more than the depositors, as it allows them to amend the losses suffered by the financial institutions by way of loans which are never recovered by big borrowers.

The bill also impacts all the fixed deposits and not only the new ones made after the bill is passed.
Some Positives of the FRDI bill would be the fact that establishes credit resolution by monitoring financial firms and banks. This could perhaps have an impact on the current fixed deposit insurance amount which is one lakh, further increasing safety for the customers. FRDI can avoid past scenarios like the fall of Lehman Bros in the US.

Points to Ponder about FRDI is that the depositor might be the biggest loser in an event the firm declares bankruptcy. As the fixed deposit can be converted to be used as Bail-in, without the consent of the customer.

The good news is that the government’s objective is to fully protect the interest of financial institutions and the depositors. With this intent, it is only a game of wait and watches to see what the standing committee decides and the financial limit on which the insurance is set for the Bail-in clause.

You must have heard many discussions on the role of a project manager and that of a business analyst. One versus the other, or one is a progression to another. Irrespective of the debate, one thing is coming out clear, that project management and business analysis are pivotal and strategic roles within an organisation.
Project Management’s key focus is on ensuring to create ‘Product, Service, along with the Impact’. The Project Manager controls the project, by applying the knowledge, skills, tools and techniques, to conduct activities that meet the project requirements.
Business Analysis’s focus is on clearly understanding the needs of the stakeholders and the business objectives, and further defining the characteristics of the solution to meeting those needs. A business analyst analysis the situation, by using techniques and tasks to liaise with the stakeholders, with the endeavour to better understand operations, structure and policies of an organisation, so that they can recommend resolutions to the organisation to meet its goal.
Apply this to a broader perspective, if you need to create project deliverables to produce expected business deliverables, it becomes imperative to first understand the business need for the change of the organisation.

Not as simple as it sounds as the stakeholders speak the business language, not necessarily as project deliverable, and they will speak in terms of solutions and not needs.
This is because they are connected like you see. One focuses on change while the other on process, however both eventually make the business inch towards desirable benefits and thus the overall business objective is met.
This fact has caught the eye of many organisations. It is now clearly understood that business analysis has become a critical competency of importance to project management. Hence getting certified as a business analyst expert can move your career in a better direction, it is beneficial specially due to the rising opportunities in the field of business analysis. Organisations have understood that with the combined skills of both disciplines, they can open the doors for superior project management capabilities.
Rather than getting lost in the conflict, with a certification in Business Analysis, organisations can now look at integrating both the roles to ensure that projects are properly carried out and directed towards creation of business value.
A certified business analyst can add value project management by clearly understanding the business needs, and further translating it into feasible project requirements, all the while maintaining involvement of the stakeholders in the project.
The Business Analysis Body of Knowledge BABOK® and the Project Management Body of Knowledge PMBOK® both the guides give insights, about how on every stage of execution, a professional with BA certification will benefit the organisation, or add value to the PMBOK® Guidelines, on not only Eliciting information from the stakeholders but will also add to the requirements expected like, Planning and Monitoring, from the Project Management point of focus.
It is interesting to know that the top three reasons of project failure, is the inability of the organisation to gather accurate requirements. Most of the issue and the core solutions are lost in transit. However, if an individual is trained as a Business Analyst, and understands how to shape project outputs to achieve intended business outcomes, then the solution arrived will not only be accurate but dynamic in nature.

2017 was not one of the best years for the IT fraternity. Indian Techies faced a lot of nightmares as the year progressed, so is the worst over or 2017 was just a glimpse of what is yet to come in 2018? The fact that India’s $160 Billion IT industry laid off more than 560,00 employees, when compared to the recession in 2008, these figures look far scarier. 2017 also witnessed low hiring rates in IT and according to some expert’s entry-level openings reduced to that of the half which was observed over the last couple of years. This impact is seen around all IT companies, from Tata Consultancy and Infosys, to mid-sized players, across have reduced their headcounts considerably.

A quick look at what lead to this…?

The signs were out there for everyone, all trade pundits had predicted a disruption in the traditional roles, digitisation and automation are the primary reasons for this commotion in IT.
Besides disruption and automation, the more fundamental problem affecting the IT industry is the lack of real skills amongst most of India’s engineering graduates, they clearly don’t have ready skills that make them employable. Indian IT companies refused to accept and change from the easy traditional money making set up, to the new and sought of alien world of Social, Cloud, Internet Of Things, etc…,
‘America First’, an ideology of President Donald Trump has also added ammunition to the existing fire. The fate of H-1B a six-year temporary work visa, which the Indian companies heavily depended on is in limbo, which has further added to India’s IT Blood Path.

The Path Ahead
It is predicted in 2018, IT giants of India like Wipro, Cognizant, Infosys, and Capgemini are facing the challenge of managing their workforce, by scrutinising their performance, and thereafter either pruning or re-skilling their workforce
A pioneer in the IT companies, Accenture, finds itself in the similar quandary, where they are suddenly faced with a new problem, that of managing a huge workforce which does not have the skills of today and is unable to learn them immediately.
You see this is a matter of productivity, what 50 programmers or analysts could do five years ago can be done with less than half the numbers of smart thinkers today, naturally, there will be a downfall in manpower requirements, the focus now is not on numbers but the number of skills.
Keeping in line with this thought, over the next two quarters, the hiring intention across the IT sector in India will further weaken. Hence it is only wise that IT professionals should not get disheartened with the news and instead look at it as an opportunity, and in the next 6-12 months, upscale their skills in areas of IT which will be in high demand. Machine Learning, Concepts of Artificial Intelligence, Cloud-Based Enterprise Resource Planning, such enabling technologies are the future of tomorrow.
A trend in hiring is noticed, where in the coming year, companies want fresh talent which is upskilled, rather than investing time in training, especially during such testing periods in IT.
This nervousness amongst the companies is not going to end soon. And the impact will be seen by all, as according to predictions by analysts, nearly 70% of roles in IT will be put to risk due to automation. These disruptions are deemed as inevitable for the next 2-3 years, as it is that long it will take to transform and adapt to new skills in demand, and a positive shift will only be seen by 2020.
India more specifically, on the other hand, will be seen as creating high-value jobs against the earlier high volumes job creation. It’s the race between Skill and Scale, and the coming years will see most companies leaning towards skills.

The role of a financial professional has evolved leaps and bounds over the last decade due to the changing nature of the business. Initially, the key expectation from a finance manager was to check accounts to analyse variance between historical performance and forecasted performance.

In doing so one could certainly answer the question about how vast the variance was, but even upon investigation could not get to the root cause of the variance. It was hence incomplete information that was available and any decision was taken would not be absolutely accurate or in the right direction, anyways this worked back then.

In recent times, decisions are taken basis a multi-dimensional approach, results are compared with different variables like economic data, customer preference, markets, and only then can we say that a strategic and informed decision is made. And in this process, Big Data Analytics is an enabler.

This entire process is demonstrating that a new trend in the financial profession has initiated, Big Data Analytics skills are no longer an additional skill set that could help you get a job, but is soon turning to a must-have skill, which has become a pre-requisite for anyone pursuing their career in finance.

Keeping up with the need, the Chartered Financial Analyst (CFA) is set to add questions on Artificial Intelligence, Automated Investment Services, and Mining Unconventional Sources of Data, as a part of their examination.

Three Primary Reasons why big data has become essential for financial services.

1. Profitability – By getting insights from the vast volumes of data, helps the financial organization to focus on target products and potential earning areas, this way they can design and launch their products for maximum returns.
2. Customer Engagement – The huge volumes of big data can give specific insights into customer behaviour and preferences, towards certain products and services offered by the bank. This will help institutions build a better relationship with the customer and in turn increase customer satisfaction.
3. Risk Mitigation – Good use of data analytics can assist banks to analyze the risk element that the financial institutions are always exposed to. They can then take the advantage of listing out potential defaulters, or risk agents and minimize the exposure to risk.

There are new areas that have developed in the financial processes where big data analytics applications can be or are used.

Procure to Pay Analytics, here data analytics ensures that updated data is maintained by the various departments, analytics also help them cross verify budgets and develop internal controls. Another process is Order to Cash, it refers to a collection of payment for goods sold and services rendered.

Predictive Analytics is perhaps the most needed by professionals which help in forecasting future revenues, preparation of budgets, hedging, cash flow etc.., each activity can be tracked for probably high and low bills, which will help them manage cash flow more effectively.

These are just a few besides, Risk assessment and Portfolio Stress Testing and other Risk Mitigating Controls that are possible due to the intervention of big data analytics.

The above-mentioned scenario is not processing what banks will do in the future; these are specific processes that are being followed by the financial institution of all statures. Due to the rapid growth in technology, there is an immense scope of analytics.

Hence staying up-to-date with the new technology is mandatory, especially for those who intend to pursue a career in finance.

New aspirants should strongly consider taking up a certification or a course in Business Analytics and Data Science to upscale their prospects.

In the field of Business Intelligence, Tableau is emerging as one of the hottest trends. The demand for professionals with Tableau experience is on the rise as the data visualisation tool is gaining much popularity in companies of all stature, big or small. Even Google trends indicate a high demand for careers with Tableau, especially if you intend to build your career in data visualisation. Getting yourself certified during the high demand, will help you take advantage of Tableau career opportunities and progress in the field of business intelligence.
The soaring demand for Tableau is not sudden, there is a logic behind it. We are currently generating great amounts of data, almost 50 times more than what was being generated, say 8-9 years ago. With the colossal amounts of data, along with real business implications, business organisations across the world would need a tool that is easy on the user end and can analyse data by deriving actionable insights from it. Now the beauty is that there are other visualisation tools available, however, Tableau does exactly that, easy to use, with excellent visualisation, thus the massive popularity. According to a research by Gartner, the popularity of tableau is going to hit the roof, also Google trends are testimony to the growth in demand for tableau professionals, especially over the past five years.
Not only is the demand high for Tableau, but also the pay packages being offered to Tableau professionals is tempting, as not only is it higher when combined with a few other skills, but is also showing an upward trend. Not only in the United States, but also in India as well, where a median salary of above Rs five lakhs is being offered to anyone with knowledge in the Tableau software, as expressed in a survey by PayScale recently.
If you survey the job sites which are on a hunt for professionals with knowledge in the Tableau Software, you will notice, not only SME’s but many fortune 500 companies are listed as well. Capgemini, ITC InfoTech, Tata Consultancy, General Motors, Sony, Bank of America, KPMG, Dell Groupon, General Motors, Facebook, are few of the top companies besides various others, who are looking for Tableau Talent, in India and their Onshore locations.
The icing on the cake while considering certification of the Tableau software is that it opens up a variety of job roles to choose from, at various levels in your professional life cycle. Some popular titles for Tableau Professionals are, Tableau Consultant, Data Analyst, Business Analyst, Business Intelligence Analyst, Business Intelligence Developer, Business intelligence Manager, amongst others.
Lastly while it is good to know that a career in Tableau is very promising at present and that picking up the skill might open several avenues for you, it is also important to note that there are a few additional skills that go hand-in-hand, and knowing them will only add to your profile once you are thoroughly proficient with Tableau. Some additional skills are, understanding how to work with Databases, a solid understanding of Statistics, Working on multi storage databases. There should always be an eagerness to learn, develop and be inquisitive in this particular field.
A professional certification or a formal training will help you use the tool more effectively and efficiently than picking up information from free available sources. A course will help you stand apart in the crowd.

 

Machine Learning usually goes synonymous with Artificial Intelligence. To generally put it, it’s a pathway which enables the computers to perform certain tasks, for example, prediction, planning, recognition, diagnosis, robot control, all without specific programming. Through machine learning algorithms are created, by the development of these algorithms a model or a program can teach itself to learn and grow, and eventually, change whenever exposed to new data.
One can draw a line of similarity between Machine Learning and Data Mining, as both search the data for patterns, while data mining extracts data for business understanding, Machine Learning notices patterns in the data and alters program actions, thus extracting data for improving the programs own understanding.
One parallel is, that you need to have an inherent quality of being inquisitive, as curiosity is a prerequisite to a profession in Machine learning. The toolbox of a Machine Learning enthusiast is quite wide-ranging, yet there are a few key non-negotiable skillsets that are essential.
Statistics and Probability theories become imperative, as these theories help in learning about the algorithms. Theories like Naïve Bayes, Hidden Markov Models are some examples. And to understand these models it becomes necessary for you to know statistics and probability.
Math and Algorithms work as a pillar to a machine learning enthusiast, as to discriminate models such as SVM’s, you need to have a firm understanding of the significance of how an algorithm works and understanding the algorithm theory.
Programming Languages become a must if you need to build a career in machine learning, more importantly, it is better if you have the working knowledge of all the languages, Python is a favourite general purpose language, R for statistics, Hadoop is Java-based so Java to implement mappers and reduces, C++ can help in speeding code up.
Data Modelling, as machine learning often requires analysing unstructured data which eventually is relied on the science of data modelling, which is basically a prose of reckoning the structure of underlying data, finding patterns, filling gaps where data is non-existent. So if your conceptual understanding of data modelling is strong, it helps create effective and efficient algorithms that can be further trained and enhanced over time.
Managing and working with large datasets is expected out of a person planning to build their career in machine learning, as these days, data is generally not processed using a single machine. A distributed computing approach is used, and data is distributed across an entire cluster.
Advanced Signal Processing Techniques is an important part of machine learning. It is not a one cap fits all type of solution that one is expected to give in machine learning, different types of problems can have various solutions. And using advanced signal processing algorithms will help you set yourself apart from the race.
Besides these skills it also becomes important for someone entering the machine learning field to keep themselves updated about the recent and future trends, so be well read, and connected with the online community, and learn about the new theories and algorithms.
The trends of 2018, like the last year, show massive promise in the field of machine learning. As a machine learning professional, one area where you will play a big role is in shaping the future of online services. Besides diverse industries are ready for innovation in this field and are on the lookout for experts and engineers. So by mastering the skills of machine learning, you will be building yourself a solid ground for the future.

It is a matter of perspective really, how do you interpret the term ‘Disruption’, in context to this blog, the term ‘Digital Disruption’. Some people’s first response on hearing the term disruption would be, inferring it as a ‘Negative’ intervention to their daily functioning of lives, specifically digital disruption, could have a connotation of a negative impact to their current form of business. But a flip side to this could be coined as a ‘Digital Opportunity’, which is only possible if you embrace the disruption or the new change in technology, which will be available in the near future and will impact your current business in one way or another. Through this blog, we have tried to explain the true inference of digital disruption and its reign in the coming years.

What is Digital Disruption?

It is nothing but a shift or a transformation that is the result of some emerging technologies and business models, with the power of impacting the value of existing technology, products or services currently offered. Hence the terminology of ‘Disruption’, as the development of new products, or services or businesses, which are digital in nature, disrupt the current market, nudging companies to re-evaluate their position.
Most IT heads and leaders find themselves facing the intimidating term of digital disruption, there initial response to it is to ‘wait and watch’ It is this very attitude that needs to change, as, with this thought, organisations face the risk of being left behind in competition.
And the reason most IT leaders are intimidated is that of past examples of disruption, the case study of Kodak, how they failed to capture the future markets and could not identify the correct threat to their business, as they failed to change with the evolving identities of their customer’s needs. Kodak could not keep up with the fact that cameras could not only be a device for taking pictures, but a friendlier and fun gadget for their clients too. Sony and Cannon took advantage of the Gadget culture and became favourites of their consumers, by introducing new technologies and approaches, while a mobile company like Nokia also entered the competition, which was unheard of at the times. Finally, as a result of holding their ground and not embracing the digital disruption, Kodak could not sustain and eventually declared Bankruptcy in 2012.
Uber, Airbnb and similar other services, are recent disruptions to the local taxi and hotel industry. The lesson that can be learned by Kodak, is that to begin with Digital Disruption is an unstoppable occurrence, and instead of fighting and waiting for its impact or denying the possibility, businesses should embrace it. And going a step ahead should also consider asking themselves, ‘how can my business become a digital disruption to others?’.
The Reign of Digital Disruption
There is a wave of change anticipated, which has the potential to redefine the very core of how businesses function. In the future one will see users changing their likings from mobile apps to virtual assistance, shopping in augmented reality will become a reality, the conjectures are big, dynamic and colossally exciting.
A study by Gartner suggests that by 2020, 100 million customers will shop in augmented reality.
30% of all browsing activity will be done in without a screen, almost 20% of the brands will abandon their mobile apps, and algorithms will alter the behavior of more than one billion global workers. And in the years after, the top seven digital giants will own 20% of all activities that an individual engages in, while Blockchain based businesses will be approximately worth $10 million. Astonishing, isn’t it?