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Tag: data analytics certification course

12 ideas for better data visualization

Posted on by Imarticus Learning

What is Data Visualization

Data visualization is an integral part of any business. It helps you see your data in a new way and makes it easier to understand trends and patterns. This blog post will discuss different ideas for better data visualization with Power BI. These tips will help you learn data visualization, create more effective charts and graphs and make your data more understandable to your customers.

Here are nine tips for better data visualization:

1. Use the correct chart for your data

There are many different types of charts and graphs available, and it can be challenging to know which one to use. When choosing a chart, ensure that it is the best type for your data. A bar chart or column chart will be a good choice if you have categorical data. A line graph or scatter plot would be better if you have numerical data.

2. Use colors to your advantage

Colors can be beneficial when it comes to data visualization. They can help highlight certain aspects of the data and make the overall visualization more aesthetically pleasing. However, it is essential to use colors wisely. 

3. Keep it simple

Complex visualizations can be challenging to understand and take time to create. Simplifying your visualizations can make them more effective and easier to interpret. 

4. Use labels and annotations

Labels and annotations can be beneficial in data visualizations. They can help explain the data and provide context for the viewer. 

5. Tell a story

A data visualization should tell a story. It should always have a beginning, middle, and end. The beginning should introduce the viewer to the data and the problem you are trying to solve. The center should effectively present the data. And the end should provide a conclusion or call to action. 

6. Choose the most compelling vision.

There are many ways to visualize data. But not all visualizations are equally compelling. When choosing a visualization, consider what type of data you have and what you want to communicate. 

7. Combine shape indicators

Indicators are a great way to show data, but they can be even more effective when combined with shapes. You can create informative and visually appealing visualizations using both shape and color.

8. Use icons or images

Icons and images can be a great way to add context to your data visualizations. They can help explain the data and make the overall visualization more visually appealing. 

9. Think about the layout

The layout of your data visualization is essential. It should also be easy to understand and interpret. The overall design should be uncluttered and straightforward. You can ensure that your visualization is practical and easy to understand by thinking about the layout.

By following these tips, you can create practical and visually appealing visualizations.

Discover data analytics courses with Imarticus Learning

This data analytics course with placement assurance is to help students learn data visualization and how to apply Data Science in the real world and create complex models that produce essential business insights and forecasts.

Course Benefits for Learners:

  • To be employable, students must have a firm grasp of what is data visualization, data analytics, machine learning basics, and the most in-demand data science tools and techniques.
  • Learners earn a tableau certification by participating in 25 real-world projects and case studies led by business partners.
  • Data science and analytics jobs are among the most in-demand skills in today’s workplace, so recent graduates and early-career professionals should consider enrolling in data science and analytics programs.

Contact us through chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon.

Why Joining A Data Analytics Certification Course Should Be Your Top Priority?

Posted on by Imarticus Learning

Why Joining A Data Analytics Certification Course Should Be Your Top Priority?

Today the world is driven by data. From small to large businesses, data rules the terms everywhere. Although it may sound cliche, the truth is that data is an asset. Why is that so? Why has data gotten so much exposure lately? Particularly in the light of AI and machine learning, data has become unquestionably significant. Let us take an example to understand the matter.

Why is data significant?

Assume ABC is a private company that sells pharmaceutical goods. During the Covid-19 lockdown, ABC sold around 5000 masks in a quarter. From 2020 March onwards, it has seen a fall in the number of masks sold. However, it has witnessed a rise in the number of hand sanitisers sold. 

Now, this is a generalised statement. You can say this as the inference drawn from overall business. What ABC would be interested in is getting a detailed report of the sales. If there is a fall in the number of masks sold, then which are the areas where it dipped the most? In the case of hand sanitisers, which are the regions with high demands for the product. These aspects can only be answered by data. Proper data maintenance and analysis will enable ABC to prepare a detailed business report. 

So you can see that data allows a business to run on numbers and figures and not on assumptions and predictions. This makes business more profitable. A thorough analysis furnishes the areas of opportunity clearly to the management.

This is a reference case study. In reality, big businesses depend entirely on data analysis. And not only business, but other fields are reliant on data massively. This, in turn, creates an ocean of opportunities for data analytics. Let’s see now why a data analytics certification course should be your top priority.

Learn Data Analytics

We are often advised to take up a course on data analytics online training. Have you ever wondered why people are so keen to learn data analytics? What are the key benefits of mastering data analytics? 

Any and all aspects of data analysis fall under this broad category of data analytics. A data analyst assists a company in building a large database for regular use, from management to storage. This sector is becoming even more dynamic with the introduction of emerging technologies. The following are the highlights of joining the best data analytics certification course. 

Data Analytics as a career

We have already seen how data analytics helps business firms and organisations with proper data structuring, data management, data storing, and data prediction. A business always requires accurate data and therefore the demands for sound data analysts are always high in the market. Other avenues are dependent on data as well. Thus, if you learn data analytics today, you will have the best job opportunities lined up for you tomorrow.

Job opportunities outside India 

Western countries adapted to data analytics much earlier. Today, they are working with big data. Big data, to put it simply, is a collection of data with varying levels of complexity, volume, and mobility. This requires in-depth knowledge of data analytics. Companies such as Apple, Google, Facebook, etc. employ the best data analysts from different parts of the world. Thus, you will be rewarded with the most lucrative job opportunities in foreign countries if you enrol in the best data analytics certification course.

Data analytics as the backbone of IT and non-IT hubs

Data analysis gives you opportunities you never would have thought about. Big IT hubs across the world are highly dependent on data analytics. On the other hand, if you think of a non-IT field, say, for instance, banking is also counting on data. For example, a bank would go through rigorous data analysis before it rolls out a new scheme in a particular area. What was conventionally referred to as a ‘survey’ in non-IT fields has become data analysis today. You can say it is the most scientific approach to perform an extensive survey based on available information.

New technologies and data analytics

One of the major advantages of data analytics is that it embraces new inventions with open arms. The intervention of new tools and new processes enriches the field and take it forward to the next phase. Many fields have become stagnant due to rigidity and lack of flexibility. However, data analytics is an agile and adapting field. This is what makes data analytics a super-sustaining field. 

Data Analytics Online Training 

If you join a data analytics certification course, you will acquire an in-depth knowledge of the subject. You will get to work with the tools of the trade, You will learn new programming languages and techniques that will polish you as a professional. Think of it as the phase when you keep collecting and storing miscellaneous weapons in your armoury. This will be handy at the time of job interviews. The more you are well-versed with contemporary tools and techniques, the higher will be your demand in the job market. 

Therefore, start your data analytics course today for a secure and prosperous future. 

Understand Quality Metrics Of Chatbot Training Data: Data Analytics Beyond Training In 2022

Posted on by Imarticus Learning

Understand Quality Metrics Of Chatbot Training Data: Data Analytics Beyond Training In 2022

A chatbot is a software or a computer program that simulates human communication or “chatter” via text or voice interactions. Chatbot analytics, also known as conversational analytics, chatbot analytics, bot analytics, and chatbot intelligence, is a valuable tool for directing business chatbot trials. This post will help you understand the quality matrix of chatbot training. 

What is chatbot analytics?

Users increasingly use chatbot virtual assistants in business-to-consumer and business-to-business environments to conduct simple tasks—chatbot analytics evaluate previous bot conversations to get insights about chatbot performance and customer experience. 

The work of a company as a chatbot developer does not finish when their bot goes online. Because of the increased competition in every business, customer experience has become a critical driver in establishing a competitive advantage. After a company introduces a chatbot, it is the right time to monitor how users interact with it.

Understand Quality Metrics Of Chatbot Training Data

Once you recognize how a chatbot works, you can use chatbot analytics and metrics to analyze its success. You can continuously monitor response time, conversion rate, and efficiency enhancement with KPIs to significantly increase it.

Goal Completion Rate: GCR is at the top of our list since it accurately assesses your chatbot’s effectiveness by collecting the proportion of successful user interactions with the chatbot.

Engaged Users: These are active users who have daily or weekly discussions with your bot. The active users recognize the value of employing your chatbot. They enjoy utilizing your bot and continue to patronize your company.

Conversation starter messages: Interactions between the consumer and the bot are bidirectional, and the number of times the bot begins the discussion serves as the foundation for the next measure.

Bot Messages: This indicates the total number of messages sent by the bot during a discussion. We want this statistic to be high since it measures the length of the dialogue between the consumer and the bot.

In Messages: This category displays the user’s messages. We need to know if the user interacts with the chatbot. We don’t need to utilize a chatbot if this category is deficient.

Miss Messages: These are messages that our chatbot is unable to process. This measure may be difficult to compute. The number of times the chatbot misinterprets the input.

Data scientists and data engineers are now among the most in-demand employment categories worldwide. Finance and insurance, retail, healthcare, information technology, and telecommunications have opened their doors to data analytics specialists.

Discover Data Science Certification with Imarticus Learning

Learn how to apply data science in the real world and create predictive models that improve business outcomes. This data analytics course with placement is suitable for recent graduates and professionals looking to advance their careers in data science and analytics. Students can now master data science skills by participating in 25 in-class, real-world projects and gaining practical experience through hackathons, capstone projects, and mock interviews.

Course Benefits For learners:

  • Learn the fundamentals of data analytics, machine learning, and the most in-demand data science tools and methodologies to become job-ready.
  • These concentrated sessions with hands-on exercises make learning more effective and efficient. 
  • Students can clear all of their doubts in live sessions and take part in discussions throughout the course.

Contact us through chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

Tech Talks: Use of Data Analytics in improving working Capital Management

Posted on by Imarticus Learning

What is working capital management?

Working capital is an organization’s utilization of money to cover its daily needs, such as paying for raw materials, supplies, and salaries. The term can also be applied to individuals. Working Capital Management is defined as “managing cash flow so that it fulfills all the business needs”.

For example, if you have $10 in your wallet but need $100 worth of groceries today, your working capital would be negative $90. Working capital management takes care of the flow of funds within the organization. It ensures that funds are available to meet short-term obligations without having to borrow or sell assets. It’s essential for all businesses because it affects the growth and the profits of the company.

Without sufficient working capital, companies will fail before utilizing their full potential. Working capital management is a critical function for every company. Whether you are operating in the manufacturing or service industry, managing your working capital will impact your ability to grow and succeed. 

How does it help the organizations?

Data analytics can help organizations measure how much money they need for their working capital based on their current situation. This way, they can improve their working capital management by minimizing risks such as overinvesting or underinvesting in one area while neglecting others.

There is a need for both MSMEs and large manufacturers to remotely manage their supply chain, cash flows, etc. This has led to a rapid and massive shift away from manual processes. This is where automation comes into play – Accounts Receivable Automation (ARA) was developed as an alternative solution by many companies who needed more control in this area of their business while still managing all aspects with less workforce. These systems allow businesses to deal directly with suppliers and it drastically cuts down processing between payments and delivery. 

Application in the real world 

In the past few years, the use of Data Analytics has been steadily increasing as a way for organizations to understand their customers better and identify trends. 

In today’s world, data analytics is indispensable as it facilitates the efficient working of an organization. The proper recording and analysis of every activity related to the manufacturing cycle of the products help in having visibility of the processes. 

One particular area where Data Analytics can be applied is in examining customer payment patterns, such as when customers pay or don’t pay on time. For example, one company found that because of the customers who paid late, they were losing roughly about $21 million annually due to delayed payments from other clients. It also examined the reasons why people pay late. They came up with several insights like cash crunch during month-ends, etc. that stopped them from making these payments. 

Using a company’s balance sheet and cash flow statement, a financial analyst can determine when the business has excess funds and also the times when they need more money. This analysis can then be used to establish an appropriate financing strategy that balances the company’s needs with its ability to repay the debt over time. Data Analytics makes the entire process smoother and better.

Conclusion

To maintain change, it is imperative to differentiate between noise and signal. This is done by developing measurable, granular  KPIs that are monitored strictly. Carefully analyzing historical data can provide valuable insights into managing networking capital by quickly finding and dealing with emerging issues.

Contact us today if you want to be well equipped when it comes to dealing with such situations. With a digital analytics course, implementing these tactics in your business becomes easier.

With a data science course, you become aware of the techniques that go into it. The course comes along with a placement opportunity so that you’re all set to apply your business analytics knowledge in managing operations.

8 benefits of Power BI for businesses

Posted on by Imarticus Learning

Businesses of all sizes are starting to realize the importance of data. To make informed decisions, you need access to accurate and timely information. It is where Power BI comes in. It allows you to visualize your data in various ways. This blog post will discuss eight benefits of Power BI for businesses. 

Power BI is a business analytics tool that enables you to connect to your data, visualize it, and share insights. With Power BI, you can get the most out of your data to make better decisions for your business.

Here are eight benefits of using Power BI:

Benefit # 01: Rich, personalized dashboards:

With Power BI, you can create rich, personalized dashboards with data visualizations unique to your business. You can include data from various sources, including Excel files, SQL Server databases, and cloud-based services like Salesforce and Google Analytics.

Benefit # 02: Seamless Integration:

Power BI integrates seamlessly with Excel, making it easy to connect to your data and get started quickly. You can use Power BI Desktop to create reports and dashboards that you can share with others.

Benefit # 03: Q&A functionality

With Power BI, you can easily ask questions about your data and get answers in return. This functionality is beneficial for businesses that want to make sure they get the most out of their data. 

Benefit # 4: No memory or speed constraints

 It means that you can quickly analyze large data sets without having to worry about your computer running out of memory or processing power. 

Benefit # 05: Collaborative features

With Power BI, you can easily collaborate with other team members. 

Benefit # 06: Drag-and-drop functionality:

Power BI also offers drag-and-drop functionality, making it easy to create visualizations and reports. 

Benefit # 07: No specialized technical support is required:

Power BI does not require any specialized technical support. It means that you can quickly get started with Power BI without having to worry about whether or not you have the right skillset. Additionally, Power BI is easy to use so that you can get started quickly and easily.

Benefit # 8: Supports Advanced Data Services:

Power BI also supports advanced data services, which means that you can easily connect and analyze your data. It is constructive for businesses to get the most out of their data.  

 If you are searching for the best technique to ensure you are getting the most out of your data, then Power BI is a tool you should consider.

Discover data analytics course in India with Imarticus Learning

This data visualization program is by industry specialists to help students master real-world Data Science applications from the ground up and construct challenging models to deliver relevant business insights and forecasts. 

Course Benefits For learners:

 

 

How to build a robust data analytics portfolio

Posted on by Imarticus Learning

Successful data teams require not just outstanding data analysis, but also a strong product and project management foundation. In this article we will tell you what should be included in a data analytics portfolio, and how here at Imarticus you can subscribe to a data analytics course with placement to obtain a data analytics certification. 

big data analytics certification coursesGood vs. great data scientists: create your products with impact

A skilled data scientist has a large learning reservoir. He knows how to design stunning dashboards. To categorize the MNIST dataset, improved NN models are built. He uses extremely complicated business algorithms that would take years to master. This is commendable, yet it is insufficient to achieve results.

A strong product and impact are required to become a successful data scientist. Products represent values that your users will appreciate. It’s a sign that your abilities had an influence on society. Finally, when you walk in for a data science interview, you must show that you can solve issues and provide value to the table.

As a result, outstanding data scientists utilize their dashboards to create prediction formulae that will halt CoronaVirus from spreading to millions of individuals. To safeguard millions of people from being hijacked, a big data scientist uses his NN model to identify phishing assaults. A big data scientist’s portfolio includes audiences, products, and impacts by definition.

What should be included in a data analytics portfolio?

There are numerous approaches to analyzing and diagnosing a client portfolio. Using 4-5 axes of analysis, which might be utilized in this manner to generate a “snapshot” of the client portfolio, is a simple and rapid technique to acquire a “snapshot.”

Customer segments are the first axis. This study will be carried out by classifying customers into categories based on their value, from highest to lowest. Basic data should be available for each client category, allowing their contribution to turnover to be easily understood. The number of clients, as well as the contribution to turnover, are examples of preliminary statistics (turnover, margin, visits, contracts, etc.). Starting with this axis allows us to adjust the offer, resource allocation, marketing, and so on. It also helps us to determine our client’s wallet share in relation to the market.

The second axis is customer status. A customer’s status indicates his or her life cycle. While segmentation gives us a “snapshot of the client portfolio,” this axis reveals how each section has evolved over time. It also helps us to evaluate client acquisition efforts, customer loyalty program performance, and so forth. In general, there are four stages in which a client can be:

  • Registered: when a consumer completes their first transaction with us.
  • Active: once they’ve made their first purchase.
  • Sleeping: after a period of “x” months with no purchase.
  • Low: After a period of “y” months without making a transaction.

The third axis is Customer Acquisition/Acquisition Reasons: Specific campaigns might stimulate a customer’s activation; the key in this axis is to understand why consumers are having their first experience (in the case of a new customer) or why they are “activated.” We will be able to determine the reasons for the growth in the value of the client base using this axis. Customer surveys, ideas, activation efforts, and customer support workers may all provide this sort of data. We may see an example of motives for acquisition-related campaigns in the diagram below.

Axis four is Non-renewal/unsubscription reasons: The reasons for churn or non-renewal allow us to determine the impact of customer non-renewal on turnover (turnover, margin, etc.). With this axis, we can see the reasons for the portfolio’s decline in value. Customer surveys, social media, and customer service workers may all provide this sort of data.

Axis 5 is Level of Recommendation: The level of recommendation allows General Management to “remain” with one number, just one, and if we have an NPS (Net Promoter Score) evaluation of the moments of truth, we will be able to identify which touchpoints have produced memorable experiences.

Conclusion

Here at Imarticus, we can offer you a data analytics course with placement to boost your career and to help you in the first steps of obtaining a data analytics certification.