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Tag: Data Analytics Training

A complete guide to data analyst training for beginners

Posted on by Imarticus Learning
Reading Time: 3 minutes

Nowadays, it is said that data drives the world. The organization with more refined data has a higher probability of making a better prediction on future business and its processes on optimization. Data being important to an institution, it is quite obvious that the analysis of such data may only lead to those future predictions, besides, of course, correcting the present-day business.

Thus, in present-day India, huge opportunities have been created for individuals who want to work on data management and analysis. This career is meant for candidates who missed out on pursuing a software engineering course but have a tremendous interest in computer software activities. A data analytics course is the best option for them to fulfil their ambition. Prospective aspirants may be undergraduates from any domain. However, it is important to understand that before choosing the course, students must also have a reasonable understanding of mathematics and statistics with basic to medium working-level know-how in Excel and PowerPoint.   

Tools for Data Analysis 

The prerequisites of learning data analytics have been mentioned above. Now let us understand the working tools of the subject. We are aware that the job of a Data Analyst is to gather, filter, segregate, clean and finally analyse data meaningfully for business owners so that they take important decisions. There are certain skill sets that the candidate has to acquire through Data Analyst training. Advanced Excel, SQL and Programming Languages like R, Python etc., are the basic skill sets that a professional in this field must possess. The above know-how shall help them to analyse the data fruitfully or even extrapolate them. However, next comes the process of visualization of the big picture.

A Data Analyst must present their findings to the business team so that they can understand the analysis as a whole. In order to make such visualization simple and user-friendly, the Data Analyst must learn tools like Power BI or Tableau.

Apart from the mentioned points, an aspiring Data Analyst must complete a few meaningful projects post completing the course. Executing projects will not only give the candidate confidence in the subject but also add immense value to their CV.  

Data Analysis Training Courses

data analytics course

There are several training courses on Data Analysis in India. Some of these courses are offline, while others are online. Since these are essentially certificate courses, the duration and the content for each also vary greatly.

However, a good Data Analyst training course will essentially cover topics on pre-processing the data, their classification, segregation and filtration. This also includes text mining and social media or site analysis. Understanding of data structures should be covered. Advanced Excel, SQL and programming languages like R or Python should be within its syllabus. The course must teach data visualization tools.

Thus, the selection of the right data analytics course is of extreme importance. A well-designed course with better content, well aligned with the right purpose, helps the aspiring candidate to learn systematically and quickly. A good mentor on the subject is also a must for a beginner. The importance of choosing the right course to build a career is all the more important since a candidate has to learn a whole gamut of skill sets of different dimensions and also their application. Since the job role involves an efficient presentation to business owners, soft skills also form a major learning topic. Students who aspire to enter the field of data analysis must understand all these parameters and introspect carefully before moving ahead. Technical skills and logical understanding are key deciding parameters for a recruitment process in this field. 

Besides, the study material should also contain statistical analysis and interferences, exploratory data analysis and basics of modelling, which will further help the candidate to complete projects successfully. 

Conclusion

There is a huge boom of information in today’s world and a matching demand in the field of data analysis. The job opportunities for a Data Analyst are vastly increasing. With proper training and future application, a candidate may even aspire to become a Business Analyst or an Operation Analyst. With the further enhancement of knowledge on subjects like artificial intelligence and machine learning, a present-day Data Analyst may also aspire to become a Data Scientist. 

An interested candidate can learn data analytics from the postgraduate program in data science and analytics course taught at Imarticus. The duration of the course is 6 months, and it is one of the best courses in India for learning data analytics. This is a placement-assured program with 1500+ candidates having already secured a position in reputed companies. This course offers both online as well as offline modes of teaching. This course will guide you towards your goal and help you become a successful data analyst. 

Training in Excel as A Data Analyst? Read On

Posted on by Imarticus Learning
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There are different opinions when it comes to training for a job in data analysis. Some people will tell you that getting a degree from a top university is the only way to succeed. Others will say that experience is more important than anything else. And still, others will tell you that specific skills, like the ability to use Excel, are what matters. So, who should you believe?

As it turns out, all three groups of people are partially right. You can gain entry with a degree from a prestigious university. And yes, experience is essential. But when it comes to landing a job as a data analyst, specific skills—like the ability to use Excel—can decide between getting an offer and passing over.

Why Excel Skills Matter for Data Analysts?

Excel is the most commonly used program in business today. That’s because it’s a potent tool for everything from keeping track of sales numbers to performing complex financial analyses. And while Excel might seem like a program that anyone can use, the fact is that most people only know how to do the basics.

 

As a data analyst, though, you need to be able to do more than just the basics. You need to be able to use Excel to its fullest potential to find trends, uncover relationships, and make predictions. In other words, you need to be an expert. And that’s why having Excel training can be necessary when looking for a job as a data analyst.

Excel Skills You’ll Need as A Data Analyst

You will learn analytical and visualization techniques in this course, which will help you improve your current work performance and your job prospects in the future. If you’re in business or data analysis and want to enhance your employability, learn advanced Excel and basic Power BI.

So what kind of Excel skills do you need to land a job as a data analyst? 

Here are just a few of the things you should be able to do:

  • Import and export data from different software programs 
  • Use basic formulas and functions 
  • Create charts and graphs 
  • Perform simple statistical analysis 
  • Write macros 
  • Use pivot tables 

As you can see, having training in Excel can give you a real leg up when you’re looking for a job as a data analyst. However, it’s important to note that simply taking an excel course is not enough—you also need to learn python online and have some experience working with data to excel in this field. Still, if you’re looking for a way to enhance your chances of landing a job as a data analyst, getting training in Excel is certainly worth considering.

Discover PG in data analytics with Imarticus Learning

 You might be able to find employment at Tableau with the aid of this data analyst training. Create complex models using data science to produce vital business forecasts and insights using what you’ve learned.

Course Benefits for Students:

  • Students will be familiar with the most common data science methodologies and tools and the fundamentals of data analytics and machine learning.
  • Students who complete 25 real-world projects and case studies under the guidance of business partners will receive a data analytics course with placement.
  • The Data Analytics and machine learning course is an intensive program that will teach you how to use data analytics to solve real-world problems.
  • One of the most in-demand skills on the market is the capacity to display data using a data analytics tool.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

What Are The New Advancements In Data Analytics?

Posted on by Imarticus Learning
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Data analytics is a field which witnesses a continuous revolution. Since data is becoming increasingly valuable with each passing time, it has been treated with great care and concern. New tools, techniques, theories, and trends are always introduced in the data analytics sector to cope with the constant changes in the industries and societies. You can opt for a sought-after data analytics course to get a deeper understanding.

In this article, we will go through some of the latest data analytics opportunities which have come up in the industry.

The Intelligent Data Mesh

The intelligent data mesh has been termed the next revolution in healthcare and medical diagnostics systems in the coming years by the Gartner Top 10 Strategic Technology Trends in 2018.

The “Intelligent Data Mesh” has been described by Gartner as a meeting point of the physical and digital worlds where humans, machines, data, and services have been entwined together into a mesh.

The purpose is to gather the benefits offered by all these individual entities into a single unit to find solutions to complex issues thought to be insolvable until now.

One major industry expected to benefit most from this system is the healthcare industry where Intelligent Data Mesh is being hailed as a game-changer in enhancing patient care.

Blockchain

Blockchain continues to be an exciting technology even in 2018 and is expected to remain so for at least another decade. New advancements are being made almost daily regarding this technology as blockchain finds wider uses in various industries with time.

It will not be wrong to describe blockchain as one of the greatest data analytics opportunities. The concept of blockchain started with the idea of a decentralized digital currency which came to be known as Bitcoin in the market.

However, even though the controversy regarding the currency rose the concept of a decentralized and open-source peer-to-peer modeled technology for storing and analysing data. The concept of blockchain is now applied in a wide range of industries with its use predicted to keep rising soon.

Artificial Intelligence

Artificial intelligence is one such data analytics opportunity which is finding widespread adoption in all businesses and decision-making applications. As per Gartner 2018, as much as 41 percent of organizations have already adopted AI into some aspect of their functioning while the remaining 59 percent are striving hard to do the same.

There is considerable research going on at present to incorporate artificial intelligence into the field of data science too. With data becoming larger and more complex with each passing minute, management of such data is getting out of manual capacities very soon. Scholars have now turned to AI for storing, handling, manipulating and managing larger chunks of data in a safe environment.

Augmented Reality

Augmented Reality is an interesting new technology coming up in recent years. As a source which facilitates the interaction between machine and humans in a unique manner, AR has the potential to be a game-changer in the field of data sciences making it another top data analytics opportunity in the future.
best big data analytics course

AR can provide for the development of simpler UIs for the man-machine interaction when merged with AI allowing the users to store and interact with data in a completely new manner.

Imagine going to an island where all your data is stored in different treasure chests and you are provided with customised keys to access the chests with your data in it. These things may be possible in the future because of the use of AR in data analytics. 

Imarticus Learning offers select best data analytics courses that not only boosts your skillset but also your career as a whole. 

Frequently Asked Questions

What is a data analytics course?

Data analytics involves examining raw data to extract valuable and actionable insights. These insights, once gleaned, serve as the basis for informed and strategic business decisions, contributing to the enhancement of overall business intelligence.

Do data analysts require coding?

Certainly, coding is a fundamental requirement when undertaking an online Data Analytics Degree. While highly advanced programming skills may be optional, mastering the basics of R and Python is crucial. Additionally, a solid command of querying languages such as SQL is indispensable for a comprehensive understanding of data analytics.

Is Python a mandate for data analysts?

Possessing a thorough grasp of Python programming proves highly advantageous for data analysts. Employers commonly anticipate proficiency in utilizing Python libraries to streamline various data-related tasks. Consequently, acquiring skills in Python emerges as a prudent and strategic career decision for aspiring data analysts.

Data Analytics in Healthcare: Can a Techie Succeed in The World of Medicine?

Posted on by Imarticus Learning
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In the modern-day, Information Technology has seeped into all sectors. Industries have adopted Data Science and Analytics to drive their work and have reaped the rewards for it. In the paradigm where Data Analysts are highly sought after in all sectors, how do they fare in the field of Healthcare?

 

Big Data Analytics courses are the perfect way for techies to break into the medical sector. It has become a tool with unlimited potential, and a Data Analytics career in healthcare is a very real and prospective opportunity.

Data Analytics is generally used to draw meaningful interpretations, find trends and predict possible outcomes from Data.

Healthcare Analytics specifically aids in avoiding preventable diseases, conducting an accurate diagnosis, predicting and combating epidemics and coming up with effective treatment strategies for diseases.

A Healthcare Analyst contributes to improving the quality of healthcare and reducing the treatment costs by automating tedious processes.

Applications of Data Analytics in Healthcare

There are many applications of Data Analytics in healthcare, and a career in the field works to implement these uses. Some of the most popular applications are:

Patients’ prediction: Healthcare Analytics can be leveraged to improve patient predictions. The past admission records can be used to discover hospitalization trends, peak times and deploy personnel accordingly.

Strategic Planning: The existing data can be used to identify patterns, conduct studies and map out strategies for extensive care and in community medicine.

Electronic Health Records:

It is one of the most popular uses of Data Analytics in Healthcare. It is used to track patient medications, treatments, progress, and medical history. Data Analytics on these can reveal more details about their medical conditions and lead to more accurate prognoses.

Predictive Analytics: Predictive Analytics is the practice of recognizing patterns and predicting probable outcomes by studying the data presently available. This can be used to improve care delivery for patients with complex medical history by using history to try and predetermine the conditions they may face in the future.

Data Analytics Careers in Healthcare

The applications of Big Data analytics in medicine are vast, and more are being uncovered every day. In this scenario, techies are being welcomed into the sector with open arms. Healthcare employs techies as Data Analysts, Informatics Consultants, Clinical Data Managers in the Quality and Performance improvement sector.

One can also get promoted to leadership positions for other Analysts as Informatics Director or Chief Medical Information Officers. All these positions come with their responsibilities as well as perks. The roles and responsibilities would also entail assistance in the proper integration of data analytics within specific healthcare areas.

Conclusion

A career as a healthcare analyst is a door that opens infinite possibilities. Not only do you get to save lives as a part of the field, but you also get to innovate and change medicine in your way.

How Can Data Analytics Help You Become a Better Entrepreneur?

Posted on by Imarticus Learning
Reading Time: 3 minutes

The data analytics industry has grown exponentially in the past decade, and more data is being generated every day. This is due to the increasing need for data and data analysis that companies are facing as their dependence on data increases exponentially.

This data, when analyzed, can be used to make important decisions for businesses and individuals alike. Data analysts not only have a skill set that can be applied to any business but also possess the ability to think critically and identify innovative solutions for problems.

The time is now for you to join a data analytics course so you, too, can reap the benefits of this thriving industry! Let’s see how.

How do Data Analytics Skills Help you Become a Better Entrepreneur?

One of the important skills for entrepreneurs is knowing how to handle data, i.e., learning data analytics skills. These skills are very versatile and practical that will enable you to handle your business & its data efficiently. Data analytic skills have not only increased in importance over the last few years but also have grown to be one of the leading industries, so it’s no surprise that individuals who know data analytics skills are in demand and have a lot of career opportunities.

Data analytics skills give you a new way to compete in the job market, one that does not hinge on your education or even some sort of innate talent. There’s always a need for more data analysts and statisticians as businesses are coming up with ways to mine their databases for insights. Nearly 50% of Data Scientists say they created statistical models last year despite having no formal training in statistics.

best data analytics courses in IndiaLearning how to efficiently analyze large sets of data can help make you stand out from other applicants who might have an impressive resume but lack experience with big data tools like Excel and R programming language.

Employers know there is value in someone who has the ability to work quickly through raw information without any previous knowledge about what it all means, which makes learning Data Analytics an attractive option for students and professionals alike.

Data Analytics skills can help with this by providing an easy-to-read breakdown of campaign success and failure rates. This will allow you to take action on your most profitable campaigns while cutting funding for any that are not profitable.

best data analytics courses in IndiaFurthermore, it can help you by providing reports on the time spent on each campaign or task that will enable you to measure how much effort is put into work. Thus, learning how to utilize data analytics training can help you become a better entrepreneur by learning what actions need to be taken or prioritized differently in order to grow your business more effectively.

Become a New-Age Data Entrepreneur with Imarticus Learning

If you want to be a better entrepreneur, it is time for you to join the Data Analytics course at Imarticus Learning. The data analytics course at Imarticus Learning is designed to keep the specific needs of today’s data-driven world in mind and will teach you the skills that can help make your business more successful.

best data analytics courses in IndiaThe curriculum includes a range of topics, from basic statistics and probability theory to advanced machine learning techniques. You can learn data analytics online at your own pace, so there’s no need to put off enrolling until you have more time or money!

This program will help you move forward in your career! For more details on Data Science Course, contact us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Unlocking The Future of Financial Analysis with Advanced Analytics!

Posted on by Imarticus Learning
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Advanced analytics involves using advanced methodologies like data science, data set analysis, and automation processes to understand business trends. It is no surprise that advanced analytics is changing the landscape of business as we know it. But, how is it doing so?

Financial Analyst CourseThis article will help you find the answer to this question and more. The following points will cover advanced analytics, its relationship with financial analysis, and how to learn financial analysis 

What is Advanced Analytics?

Advanced analytics uses statistical methods, predictive modeling, process automation, and machine learning (ML) techniques that are well ahead of conventional business intelligence tools to analyze the required data. Advanced analytics employs data science and its sophistical techniques of analysis to forecast future trends and predict the probability of potential occurrences.

Simple analytics and BI can only give a snapshot of an organization. On the other hand, advanced analytics allows you to predict future trends or the most probable outcomes of a business decision. It equips you with a wider range of capabilities so you can overcome the issues present in conventional analytics.

How Advanced Analytics Enhance Financial Analysis?

Advanced analytics expands on the technologies and techniques used in business intelligence and analytics by incorporating more sophisticated methods. It can improve any implementation of analytics including financial analysis. Some of its prominent applications in the financial sector are:

Automating financial analytics

Financial analytics consists of many procedures such as creating datasets and updating the existing ones. It also involves data collection and generating reports. Advanced analytics training can help in automating all of these procedures.

By using advanced analytics, you can build datasets that can update their macroeconomic data automatically. This includes inflation, basic interest rate, and other data points. Similarly, it can help you collect data from financial statements automatically by using APIs.

Making predictions

Financial forecasting is a major aspect of financial analytics. Companies rely on it to make crucial decisions, evaluate risk, and analyze investments. Advanced analytics utilizes machine learning models that can help you perform predictive analysis.

You can build models that can adapt to the changes in financial and economic domains automatically and can make recommendations based on their insights to help in decision making.

Advanced analytics improves the data collection process by using more sources and completing the task much quicker.

Optimize current implementations

Using advanced analytics can help businesses improve the efficiency of many of their processes. It allows them to automate multiple procedures which require staff and time. Automated tasks have fewer chances of making mistakes as machines do not get fatigued. Companies can allocate the time and resources saved by all of this in other areas that require more attention.

How to Learn Financial Analysis?

Financial analysis has many applications for advanced analytics. The field is ripe with opportunity and the technology is relatively new. It allows companies to get ahead of their competitors and become a leader. Due to these reasons, the demand for a skilled financial analyst who is familiar with advanced analytics implementations is exponentially high.

The most effective and efficient method to become a financial analyst is by taking a financial analyst course. A financial analyst course will help you learn the skills required to become a professional in this field and get certified. It offers a structured curriculum so you can learn the subjects in a timely manner and plan your studies accordingly.

Taking a course will help you stand out from your peers and become a preferred candidate for financial analysis roles.

Financial analytics is a broad sector and the rising popularity of advanced analytics is transforming this field considerably. If you are interested in becoming a financial analytics professional, you must have a strong grasp of advanced analytics. It would help you boost your career growth.

Top 7 Reasons to Convince You To Take on that Data Analytics Job

Posted on by Imarticus Learning
Reading Time: 3 minutes

 

It’s more than just a buzzword, it’s a revolution– data analytics is here and here to stay. For four years in a row, data analytics was ranked the best job in the U.S. alone by Glassdoor in 2019. The data fever is catching on in other parts of the world too, as global economies become more interdependent and related.

More and more companies and industries are embracing data analytics, not least because it’s a science that delivers valuable insights applicable across all plans including business and marketing.

If you’re still hesitating about whether to go for a career in data analytics, allow these top 7 reasons to convince you:

#1: It’s in demand

Data analytics is one of the most in-demand jobs in the world today. This is because all industries need data-driven insights to make even changes, be it to pick a marketing option during A/B testing or rolling out new products. Data analytics is a high-skills, high-stakes job, which is why companies are ready to hire those willing to think creatively and derive data-based solutions to business problems.

#2: It’s easy to start

Educational institutions and course providers have sat up and taken notice of the demand for data analysts, leading them to introduce related training courses. Regardless of whether you’re a fresher or a professional in the tech field, data analytics training can help you start from scratch and build a portfolio of projects to showcase your skills These courses also provide tutorials in essential data analytics software such as Hadoop, Sisense and IBM Watson.

#3: There are plenty of job roles

Within the data analytics field, there are job roles that span academic divisions and aren’t restricted to engineering or software alone. Data scientists, systems analysts and data engineers will benefit from a background in the aforementioned academic fields. However, statisticians and digital marketing executives can look into roles such as quantitative analysts, data analytics consultants and digital marketing managers to put their skills to good use.

#4: The pay is good

The average salary in the data analytics field is US$122,000– a testament to how in-demand the profession is and how in dire need companies are of skilled employees. The figures vary depending on the role and job description but suffice to say that the pay is often much better than other technical jobs that people still seem to hover to by default. It’s also dependent on what industry you will work for, in what capacity and towards which goals.

#5: Growth opportunities abound

Technology is a dynamic field and with new changes come the chance to upskill, pick up new software and contribute to futuristic projects. Data analytics professionals can find themselves growing through roles and projects, oftentimes being tasked to lead a team or be the sole owner of a large-scale project.

#6: Industries are interwoven

With other tech fields, you might be restricted in your tasks or limited to a company. In data analytics, however, you get to pick and choose the fields you want, whether pure tech or even retail. Data analytics is in use across most industries so, once you find your niche, you’re ready to start dabbling in the industry of your choice.

#7: Influences decision-making

If you’ve ever wanted to be part of the larger organizational or business structure and contribute positively, chances are data analytics might be the niche for you. The insights that emerge from analyses of data can power strategies and create new business plans. This way, your contribution leads to progress on an organizational scale and your work can make or break a business.

Data analytics gives you the opportunity to become a more active stakeholder and contributor to any business regardless of the industry, so take the leap today.

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

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Introduction

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

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

Career In Data ScienceWhy now is the Right Time?

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

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

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

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

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

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

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

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

Why Business Intelligence Has A Role in The World Of AI?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Have you ever wondered why the sight of black cobra doesn’t scare an infant or a two-year-old baby, but it does scare a child of age 10 or an adult? The answer lies in the adrenalin hormone, secreted by a human body.

We human beings are trained for certain stimuli but if we encounter something new, we may not be able to respond well to the situation. In technology, AI is meant to think like humans by giving it the required amount of training. This training can be given by exposing the AI to a certain amount of data.

To learn business intelligence in detail and understand the role of BI technology in AI, it is very important to understand the exactness of BI and AI and the difference between the two.

Business Intelligence Role in AI

Underlining difference between Business Intelligence and Artificial intelligence

The base function of AI is to think and act like humans whereas the base function of BI is data analysis. The role of AI lies in decision making, whereas the role of BI lies in preparing the reports. The key role of BI is to collect the information, which the organizations can use to make optimized decisions. AI on the other hand uses the organization’s own information along with the information of the industry as a whole, to help the organizations to make the best possible moves.

For example, a simple tool that can convert handwritten text into typed text first uses the general information provided to it. This tool works using AI. Initially, this AI is exposed to a certain amount of handwritten text and it converts it into the typed text. Once the output is there, it requires some manual corrections to train the AI. Next time with a similar input, the output comes out in a better way. For the purpose of decision making, BI provides firsthand information to the AI to work, and later AI is trained to perform in a better way.

To understand the role of BI in AI, let us look at some examples of AI solutions

DOMO is a business management software company. This company has created a cloud-based dashboard that receives data from different apps using approximately 400 software connectors. This data is used for business intelligence.

This way, companies using DOMO can extract the data from different apps such as Salesforce, Shopify, etc. to gain insight into the customer’s sales or product inventory. The extracted data can also be used to spot the trends in the performance of the product. Later, a new feature known as Mr. Robot was added to the dashboard of Domo. The purpose of Mr. Robot is to provide insights to make decisions. This way BI is used to fuel AI.

Complementary nature of BI and AI

 There are certain patterns in the data that humans and BI cannot detect easily, the much-detailed algorithms with a consistent focus on certain parameters can help in the detection of such patterns are helping the decision-makers in a much holistic way.

Considering that the AI is superior to BI in all ways will not be correct. If all the possible constraints are not introduced to the AI, then relying on AI could result in business loss. Similarly, BI can also be extremely useful for decision-makers if the problem is unique, because of the generic nature of AI, which means it is trained to solve general problems.

Despite all the plus points, there always remains a threat to privacy breaches and data security with AI. However, with BI two major issues are organization and its people and data with technology. By considering all the positives and negatives of two systems, it is quite clear that BI in AI helps the organizations to review the data of the past and helps with new features. This helps in saving a lot of time in which organizations spend on data analysis and decision making.

What Are the 6 Applications of Predictive Analytics in Business Intelligence?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Understanding Predictive Analytics

The data science discipline has gained huge popularity among corporations given its ability to decode insights from seemingly irrelevant pieces of daily information. Data analytics training is in high demand given the paucity of professionals in the field of data science. Predictive analytics can be understood as a highly advanced version of analytics that is being used to make predictions about unforeseen future events.

The predictive analytics process entails a range of statistical methods like data mining, machine learning, predictive modeling, etc. All these methods are applied to analyze historical and current data to make future predictions. Let’s jump over to some of the most prominent applications of the predictive analytics method in the field of business intelligence.

Audience Targeting 

With the advent of advanced analytics methods like predictive analytics, the marketing game has changed. Audience targeting is all about the personalization of marketing communication with the customer. Here a customer base is segregated into groups based on extensive factors other than the commonly used age, gender, occupation. These factors might include interest, likes, spending habits, transaction history, etc. This helps companies to customize their messaging as per the audience profile and predict those who are more likely to purchase the goods or services.

Risk Analysis

The risk analysis process is a complex one and it plays a huge role in the success of any business venture. It helps to analyze and predict the problems which might occur for a business based on a complex understanding of the variables that affect the business. Predictive analytics is used in this context to help build decision support systems that can help determine the profitability of any business operation. A possible application of this technique is in the banking sector for analyzing the credit risk of borrowers. The variables related to borrowers are factored in to derive conclusions.

Revenue Forecast

Sales forecasting is an important aspect of business intelligence. Any given corporation has to think about the revenue that it’ll generate in the near future. The sales forecast is a complex process involving a lot of variables that influence the sales figures. These variables might include seasonality, market events, macroeconomic factors, general industry trends, etc. Data mining techniques can help assess consumer preference and outlook after factoring in all these variables. The end goal is to predict the demand for a given product or service produced by a firm.

Churn Avoidance 

The cost of acquiring a new customer for any business is far greater than the cost of retaining an existing one. This is why churn prevention is important for enterprises. Churn prevention helps to analyse and predict when and why customers decide to switch to other brands and end their relationship with the company. The companies can maintain a proactive approach to retain their existing customer using predictive analytics by leveraging big customer data sets.

Financial Modelling

The main goal of financial modelling is to create a simplified model of the complex real-world financial landscape that will help to predict and assess the performance of various financial assets. These are mathematical models designed to represent the quantitative performance of financial assets in the near future. In simpler terms, it is all about converting the hypothesis and assumptions regarding the financial markets into numeric figures that represent performance.

Market Analysis

The 21st-century businesses are all about understanding the needs and wants of customers and providing adequate solutions in terms of products and services. It’s far from the traditional business approach of forcing a product or a service using rigorous marketing. Understanding consumer needs requires conducting surveys. Market analysis using surveys helps businesses to understand their customers better, this results in increased profitability and high customer retention.