#Data Visualisation With Tableau

[zora28]

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[cavillionlearning]

Industry-Leading Visualization with Tableau Data Visualization

1. User-Friendly Interface: The intuitive design allows anyone to easily start visualizing data.

2. Seamless Integration: Connects easily with various data sources for efficient analysis.

3. Quick Insights: Generate actionable insights within minutes.

4. Integrated Collaboration Tools: Share dashboards and insights with your team effortlessly.

5. Regular Updates: Tableau continuously evolves with new features and improvements.

Want to take your skills to the next level? Join our 1-day Tableau Bootcamp on 2nd November (Online)!

[techsoulculture]

Using Tableau for Data Visualisation - A Guide 2023

Data visualization is a powerful tool that enables us to visually depict complex data, making it easier to grasp and interpret Tableau

[yourdreamilymassivebouquetthings]

Hi Friends,

Tableau is a trending BI tool in current job market which allows us to convert data into pictorial representation. To know more about it, please check out this tutorial. It helps you to understand what Tableau is , how and where it can be used. How easy it is to plug in and use this tool for your analysis and get business insights in few minutes.

Don't forget to like , share and subscribe. Thanks for watching. Have a nice day :)

[kikusharda123]

Learn to Clean, Visualise, and Analyse Real-World Data

In today's digital-first world, learning to work with real-world data is not just a bonus skill—it's a must. Every industry relies heavily on data-driven decision-making, from healthcare to retail, education to finance. But raw data is rarely perfect. To unlock its value, one must know how to clean, visualise, and analyse it effectively.

Even if you're a beginner or an experienced analyst, these tips and tricks will help you reach the level you desire. When going for a data science certification in Pune, it is recommended that one’s training focuses on the following three areas.

Let me explain each step in detail with real-life examples to make the work easier to understand.

Why Cleaning Data Matters

Also, it is vital and accurate to note that raw data is often filled with various errors, such as missing values and inconsistencies in the results. A lack of cleaning may cause incorrect conclusions when analyzing data, as it will contain irrelevant information.

Real-Life Example:

For your purpose, assume that you have been provided with customer feedback data of an e-commerce platform. It is dangerous to make decisions based on such data because 20% of the email addresses are incorrectly formatted, and 15% of the fields related to feedback data are empty.

Key Steps in Data Cleaning:

Assume safely that there are no redundant values stored in the form; therefore, it is recommended to check and eliminate such entries.

Dealing with missing values can be addressed in different ways, depending on the circumstances that led to the missing data. This can be done by filling in the missing values with the mean, median, or by ignoring them.

Review for errors: These include spelling mistakes, syntax, and the use of incorrect formats, especially in dates.

Check for Coherence: Inability to maintain overall homogeneity, including consistency of units of measurement.

As a learner in the data science training in Pune, you would be able to handle datasets in the training mode, which will enable you to work on live datasets that you are likely to encounter in your working environment.

Visualizing the overwhelming volume of information we come across on the internet can often appear daunting. The task of visualising the vast amount of information one encounters on the internet. The process of making the loads of information more comprehensible.

The second step that follows data cleaning is the visualisation stage. Data presentation for Game Reporting Executives transforms data into a narrative — a method of making information easy to understand and use.

Real-Life Example:

One of the latest up-and-coming companies from Pune did the same for tracking customer acquisition costs. Thus, when presented with the data in the form of bar charts and heat maps, they were able to discover that Instagram campaigns yield a 40% better return on investment than email marketing.

Popular Visualisation Tools and Techniques:

Charts and Graphs: Bar charts, pie charts, line graphs, and scatter plots help spot patterns easily.

Dashboards: Create interactive dashboards to monitor KPIs in real-time.

Heatmaps: Useful for understanding intensity across variables, such as customer activity on a website.

Infographics: Simplify large datasets into visually appealing formats for presentations or reports.

Joining a data science course in Pune often gives you access to advanced tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn, helping you master the art of visual storytelling.

Analysing Data: Finding Insights and Driving Decisions

Data analysis is where the magic happens. After cleaning and visualising, the next goal is to extract meaningful insights that can influence real-world decisions.

Real-Life Example:A hospital chain used historical patient data to predict peak admission times. Through regression analysis and time-series forecasting, they optimised staff allocation, reducing patient wait times by 25%.

Standard Data Analysis Techniques:

Descriptive Analysis: Summarising data to understand “what happened.”

Diagnostic Analysis: Digging deeper to find out “why it happened.”

Predictive Analysis: Using statistical models to forecast “what might happen.”

Prescriptive Analysis: Suggesting actions based on predictive outcomes.

As part of a data science certification in Pune, you will engage in projects where you analyse real-world datasets — from predicting sales to identifying customer churn.

Integrating Cleaning, Visualisation, and Analysis: The Complete Process

While each of these steps can be powerful individually, their true strength lies in their integration. A successful data project typically follows a workflow like:

Import and Inspect Data

Clean and Prepare Data

Visualise Trends and Patterns

Analyse and Model Data

Communicate Insights to Stakeholders

If you're pursuing data science training in Pune, you'll likely work on capstone projects where you complete the entire pipeline, simulating real-world workplace challenges.

Tips to Excel at Handling Real-World Data

Practice Regularly: Work on diverse datasets from different industries.

Stay Updated: Learn the latest data cleaning, visualisation, and analysis tools.

Collaborate: Participate in data science communities and hackathons.

Document Your Work: Always keep track of the cleaning and transformation steps for reproducibility.

Many professionals in Pune choose to enhance their skills through a structured data science course in Pune that emphasises practical learning over theory.

Conclusion

Learning to clean, visualize, and analyze real-world data is a transformative skill that can open up numerous career paths. Whether you aim to become a data analyst, data scientist, or business intelligence expert, mastering these three steps is non-negotiable.

Selecting a data science certification in Pune can be the perfect launchpad to build these capabilities. With abundant real-world projects, expert mentorship, and a vibrant tech ecosystem, Pune offers everything an aspiring data professional could wish for.

So, if you're ready to work with real-world messy data, tell compelling data stories through visualisations, and drive powerful decisions through analysis, now is the time to begin your journey. Find the right data science course in Pune and start building the skills that the future demands.

[yasirinsights]

Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer: Choose Your Perfect Data Career!

In today’s rapidly evolving tech world, career opportunities in data-related fields are expanding like never before. However, with multiple roles like Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer, newcomers — and even seasoned professionals — often find it confusing to understand how these roles differ.

At Yasir Insights, we think that having clarity makes professional selections more intelligent. We’ll go over the particular duties, necessary abilities, and important differences between these well-liked Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer data positions in this blog.

Also Read: Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer

Introduction to Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer

The Data Science and Machine Learning Development Lifecycle (MLDLC) includes stages like planning, data gathering, preprocessing, exploratory analysis, modelling, deployment, and optimisation. In order to effectively manage these intricate phases, the burden is distributed among specialised positions, each of which plays a vital part in the project’s success.

Data Engineer

Who is a Data Engineer?

The basis of the data ecosystem is built by data engineers. They concentrate on collecting, sanitising, and getting data ready for modelling or further analysis. Think of them as mining precious raw materials — in this case, data — from complex and diverse sources.

Key Responsibilities:

Collect and extract data from different sources (APIS, databases, web scraping).

Design and maintain scalable data pipelines.

Clean, transform, and store data in warehouses or lakes.

Optimise database performance and security.

Required Skills:

Strong knowledge of Data Structures and Algorithms.

Expertise in Database Management Systems (DBMS).

Familiarity with Big Data tools (like Hadoop, Spark).

Hands-on experience with cloud platforms (AWS, Azure, GCP).

Proficiency in building and managing ETL (Extract, Transform, Load) pipelines.

Data Analyst

Who is a Data Analyst?

Data analysts take over once the data has been cleansed and arranged. Their primary responsibility is to evaluate data in order to get valuable business insights. They provide answers to important concerns regarding the past and its causes.

Key Responsibilities:

Perform Exploratory Data Analysis (EDA).

Create visualisations and dashboards to represent insights.

Identify patterns, trends, and correlations in datasets.

Provide reports to support data-driven decision-making.

Required Skills:

Strong Statistical knowledge.

Proficiency in programming languages like Python or R.

Expertise in Data Visualisation tools (Tableau, Power BI, matplotlib).

Excellent communication skills to present findings clearly.

Experience working with SQL databases.

Data Scientist

Who is a Data Scientist?

Data Scientists build upon the work of Data Analysts by developing predictive models and machine learning algorithms. While analysts focus on the “what” and “why,” Data Scientists focus on the “what’s next.”

Key Responsibilities:

Design and implement Machine Learning models.

Perform hypothesis testing, A/B testing, and predictive analytics.

Derive strategic insights for product improvements and new innovations.

Communicate technical findings to stakeholders.

Required Skills:

Mastery of Statistics and Probability.

Strong programming skills (Python, R, SQL).

Deep understanding of Machine Learning algorithms.

Ability to handle large datasets using Big Data technologies.

Critical thinking and problem-solving abilities.

Machine Learning Engineer

Who is a Machine Learning Engineer?

Machine Learning Engineers (MLES) take the models developed by Data Scientists and make them production-ready. They ensure models are deployed, scalable, monitored, and maintained effectively in real-world systems.

Key Responsibilities:

Deploy machine learning models into production environments.

Optimise and scale ML models for performance and efficiency.

Continuously monitor and retrain models based on real-time data.

Collaborate with software engineers and data scientists for integration.

Required Skills:

Strong foundations in Linear Algebra, Calculus, and Probability.

Mastery of Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn).

Proficiency in programming languages (Python, Java, Scala).

Knowledge of Distributed Systems and Software Engineering principles.

Familiarity with MLOps tools for automation and monitoring.

Summary: Data Engineer vs Data Analyst vs Data Scientist vs ML Engineer

Data Engineer

Focus Area: Data Collection & Processing

Key Skills: DBMS, Big Data, Cloud Computing

Objective: Build and maintain data infrastructure

Data Analyst

Focus Area: Data Interpretation & Reporting

Key Skills: Statistics, Python/R, Visualisation Tools

Objective: Analyse data and extract insights

Data Scientist

Focus Area: Predictive Modelling

Key Skills: Machine Learning, Statistics, Data Analysis

Objective: Build predictive models and strategies

Machine Learning Engineer

Focus Area: Model Deployment & Optimisation

Key Skills: ML Frameworks, Software Engineering

Objective: Deploy and optimise ML models in production

Frequently Asked Questions (FAQS)

Q1: Can a Data Engineer become a Data Scientist?

Yes! With additional skills in machine learning, statistics, and model building, a Data Engineer can transition into a Data Scientist role.

Q2: Is coding necessary for Data Analysts?

While deep coding isn’t mandatory, familiarity with SQL, Python, or R greatly enhances a Data Analyst’s effectiveness.

Q3: What is the difference between a Data Scientist and an ML Engineer?

Data Scientists focus more on model development and experimentation, while ML Engineers focus on deploying and scaling those models.

Q4: Which role is the best for beginners?

If you love problem-solving and analysis, start as a Data Analyst. If you enjoy coding and systems, a Data Engineer might be your path.

Published By:

Mirza Yasir Abdullah Baig

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[awsqualitytechnologies]

A Complete Guide to Salesforce Consulting Services for Startups and Enterprises

Introduction: Why Businesses Rely on Salesforce Consulting Services

In an increasingly digital world, customer relationships and operational efficiency determine whether a business thrives or struggles. Salesforce, the world’s #1 CRM platform, empowers companies to streamline operations, improve customer engagement, and drive growth.

But implementing Salesforce effectively isn’t just about installing software—it’s about aligning the platform with your unique business goals, workflows, and growth strategy.

That’s where Salesforce consulting services come in.

Whether you're a fast-growing startup or a large-scale enterprise, working with the right Salesforce Consulting Partner can make all the difference—especially in competitive markets like the UK, London, and Germany.

What Are Salesforce Consulting Services? Salesforce consulting services refer to a suite of expert-driven solutions designed to guide businesses through every phase of Salesforce adoption. These services are crucial for making sure that your CRM investment leads to real business results.

Common Salesforce Consulting Services Include:

Salesforce implementation: Is the process of configuring Salesforce products such as Marketing Cloud, Service Cloud, or Sales Cloud.

Customisation & Development: Building custom objects, workflows, and automation tailored to your needs.

Third-party Integration: Connecting Salesforce with ERPs, payment systems, eCommerce platforms, or analytics tools.

Data Migration & Cleansing: Securely transferring data from legacy systems while maintaining data quality.

Training & Support: Ensuring your team is confident using Salesforce with proper onboarding and helpdesk support.

Optimisation & Upgrades: Enhancing the system over time as your business evolves.

Why Startups Need Salesforce Consulting Services Startups are innovative but often lack in-house technical capabilities. Salesforce consulting helps them:

Build a scalable CRM foundation: One that can evolve as the business grows.

Automate daily operations: From lead capturing to email marketing and sales tracking.

Gain deep customer insights: Using reports and dashboards to improve decision-making.

Ensure smooth integrations: With platforms like Mailchimp, QuickBooks, Stripe, or Shopify.

Challenges Startups Face Without Consulting:

Challenge

How Consulting Helps

Limited Technical Resources

Certified consultants handle the implementation and maintenance

Risk of Poor User Adoption

Consultants offer personalised training and change management

High Customisation Needs

Experts build industry-specific workflows and solutions

Budget Constraints

Consultants help you optimise costs through tailored solutions

Why Enterprises Need Salesforce Consulting Services Large companies use Salesforce at scale across multiple departments and regions. Their needs are complex and require expert guidance.

Key Benefits for Enterprises:

Advanced Reporting & Forecasting: Gain insights into customer journeys and sales pipelines.

Global Data Governance: Ensure compliance with GDPR and other regulatory standards.

End-to-End Integration: With tools like SAP, Oracle, Microsoft Teams, and Slack.

Continuous Optimisation: Keep the system aligned with evolving business goals.

AI & Automation: Use Salesforce Einstein to make predictions and automate tasks intelligently.

Top Salesforce Products Startups & Enterprises Should Use

Product

Purpose

Sales Cloud

Automate sales processes and manage pipelines

Service Cloud

Provide superior customer service and support

Marketing Cloud

Automate email, social, and ad campaigns

Commerce Cloud

Manage B2C and B2B online shopping experiences

Experience Cloud

Build customer portals, partner hubs, and apps

Pardot (Account Engagement)

B2B lead nurturing and scoring

Tableau Analytics

Advanced data visualisation and business intelligence

Pro Tip: A Salesforce Consulting Partner can help you choose the right mix of products based on your industry and goals.

How to Choose the Right Salesforce Consulting Partner in the UK, London, or Germany

1. Industry ExperienceChoose a partner with proven experience in your industry—whether it’s healthcare, fintech, education, or retail.

2. Certified Salesforce ProfessionalsEnsure the partner has certified Salesforce Admins, Developers, Architects, and Consultants.

3. Local Market UnderstandingPartners familiar with European business laws, compliance (like GDPR), and cultural nuances deliver more aligned solutions.

4. Agile & Transparent ProcessYour partner should follow Agile methodology, communicate clearly, and be accountable at every stage.

5. Client Reviews & Case StudiesAlways look for partners with 5-star reviews on platforms like Clutch, [G2], and [TrustPilot].

AwsQuality Technologies checks all these boxes and offers tailored Salesforce solutions for both startups and enterprises in Europe.

Real-World Success: AwsQuality’s Global Impact

💼 Client in Germany: Helped a logistics company integrate Salesforce with SAP, reducing data processing time by 45%.

📈 Startup in London: Implemented Salesforce Essentials and integrated it with Mailchimp, boosting lead conversion by 60%.

🏥 Healthcare SME in the UK: Customised Service Cloud for patient management and built HIPAA-compliant workflows.

Want similar results? Let’s talk → info@awsquality.com

Wrapping-Up: – Your Success Starts with Smart Decisions

In today’s fast-paced digital landscape, Salesforce is the cornerstone of modern CRM strategies. However, only with professional consultation can its full potential be realised. Whether you're a UK startup aiming for fast deployment or a German enterprise looking to streamline complex workflows, Salesforce Consulting Services offer the personalisation, integration and scalability your business needs to thrive. With certified professionals and deep industry expertise, AwsQuality Technologies stands out as a trusted Salesforce consulting partner across the UK, London and Germany. From enhancing customer engagement to driving automation, their tailored solutions deliver measurable ROI and long-term success. Choosing the right consulting partner not only accelerates your growth but ensures your CRM evolves with your business goals.

📢 Ready to transform your business with Salesforce? 💡 Book your free consultation today! 📧 Email: info@awsquality.com 🌐 Website: www.awsquality.com

✅ Quick FAQ – Salesforce Consulting Simplified

What exactly do Salesforce consulting partners do? They help businesses plan, implement, customise, and maintain Salesforce so it works perfectly for their unique needs—saving time and increasing ROI.

Is Salesforce consulting really necessary for startups? Yes! Startups benefit from expert setup, automation, and integrations without needing a full in-house tech team. It sets them up for scalable growth.

What challenges can consulting solve for enterprises? From global compliance (like GDPR) to complex integrations and real-time analytics, consulting ensures large-scale Salesforce deployments run smoothly.

Why choose AwsQuality as a partner? AwsQuality offers tailored solutions, certified experts, and a strong track record in the UK, Germany, and London—making them a reliable choice for startups and enterprises. Read more- https://medium.com/@thakurjibless/a-complete-guide-to-salesforce-consulting-services-for-startups-and-enterprises-b5b8d7e4ee93

[pink-city-to-datascience-city]

How Data Science Can Skyrocket Your Salary Growth

In modern society, information is power, and businesses will be more than willing to employ people with analytical skills to work on it. This article is good for the person who wants to change their career or just wishes to earn more money, and data science is one of the more rewarding careers.  

To answer the latter question and understand how data science can increase your income, let us then define some of the key components of data science below. And what actions have to be taken to be able to enter the sphere? In this write-up, I will provide all the information about how data science can augment your earnings if you want to take a Data Science course in Jaipur.  

Why Data Science Pays So Well  

1. High Demand and Low Supply  

With the recent surge in the popularity of data science, the industry is facing a significant shortage of professionals with the requisite skills. Sectors such as finance, healthcare, e-commerce, and IT are leading the charge in hiring data scientists, driving up the salary rates due to this scarcity.  

For instance, in a report by Glassdoor, data scientists are some of the best-paid tech workers across the world. Data Scientists, right from the fresher's, start with an average package of around 6-8 lakhs per annum, and those who have experience generally earn more than 20 lakhs per annum.  

If you are already located in Rajasthan and seeking to work on this opportunity, you need to undertake data science training in Jaipur to equip yourself with the right skills and knowledge of the field.  

 2. Salary Hikes Across Experience Levels  

In contrast to most professions, data science does not tend to stagnate pay in a few years. Below is a general guide to the wage escalations:  

Entry-Level (0-2 years): ₹6-8 LPA  

Mid-Level (3-5 years): ₹12-15 LPA  

Senior-Level (5+ years): ₹20-30 LPA  

Leadership Positions (10+ years): ₹50 LPA and beyond  

Such a growth pattern is unique to data science and is not commonly found in other domains. Uniqueness often intrigues practitioners in other fields, such as software development or marketing channels, and is pursued for the sake of monetary gains. 

If you want to fast-track your career, a structured data science course in Jaipur can provide you with hands-on training and help you land high-paying job roles faster.  

Key Skills That Increase Your Salary in Data Science  

Not all data science professionals earn the same. Your salary depends on your expertise in key areas like:  

 1. Machine Learning and AI  

Companies are investing heavily in artificial intelligence and automation. If you specialise in machine learning and deep learning, your salary potential increases significantly.  

For instance, data scientists with AI expertise earn 20-30% more than those without it. Many data science institutes in Jaipur now offer specialized training in AI and ML, helping professionals land top-tier jobs.  

 2. Big Data and Cloud Computing  

With massive amounts of data being generated every second, companies need professionals skilled in handling big data. Tools like Hadoop, Spark, and cloud platforms (AWS, Google Cloud) are highly valued in the industry.  

If you're considering data science training in Jaipur, look for courses that cover these technologies, as they can significantly boost your employability and salary prospects.  

 3. Business Intelligence and Analytics  

Data science isn't just about coding—it's also about deriving actionable insights. If you understand how to translate data into business strategies, your value in the job market increases.  

Companies prefer data scientists who can:  

Present insights in a way that decision-makers can understand  

Use visualisation tools like Tableau and Power BI  

Work on real-world business problems  

A data science course in Jaipur that includes business intelligence training can help you stand out in the job market.  

Industries Offering the Highest Salaries in Data Science  

Your salary also depends on the industry you work in. Some sectors pay significantly higher than others.  

 1. Finance and Banking  

Banks and financial institutions use data science for fraud detection, risk analysis, and investment strategies. Professionals in this field often earn between ₹12-25 LPA, even at mid-career levels.  

 2. Healthcare and Pharmaceuticals  

With AI-driven drug discovery and predictive healthcare models, data science is transforming healthcare. Salaries in this sector are highly competitive, often exceeding ₹20 LPA for experienced professionals.  

 3. E-commerce and Retail  

Companies like Amazon, Flipkart, and Myntra use data science for recommendation systems, customer behavior analysis, and demand forecasting. Salaries in this sector range from ₹8-20 LPA.  

 4. IT and Software Services  

Tech giants like Google, Microsoft, and TCS are always on the lookout for skilled data scientists. If you're already in IT and want a pay raise, a data science course in Jaipur can be a great way to transition into higher-paying roles.  

 How to Maximize Your Salary Growth in Data Science  

 1. Get Certified from a Reputable Institute  

Self-learning is excellent, but structured training accelerates your career. Many companies prefer candidates who have completed industry-recognized data science training in Jaipur.  

Before enrolling, compare data science course fees in Jaipur and choose a program that offers:  

Hands-on projects  

Placement assistance  

Certifications from recognised organisations  

 2. Build a Strong Portfolio  

Employers value practical experience. Work on real-world datasets, participate in Kaggle competitions, and showcase your projects on GitHub.  

 3. Keep Learning Advanced Tools  

Data science is an evolving field. Stay updated with:  

New machine learning algorithms  

Advanced statistical methods  

Programming languages like Python and R  

 4. Network and Apply Strategically  

Engage with the data science community on LinkedIn, attend industry conferences, and apply to companies that value data-driven decision-making.  

Final Thoughts: Is a Career in Data Science Worth It?  

If salary growth is a priority for you, data science is one of the best career choices. With high demand, lucrative pay, and diverse career paths, it offers professionals the opportunity to grow financially and professionally.  

If you're serious about entering this field, enrolling in a data science course in Jaipur can be your first step. Compare data science course fees in Jaipur and choose a program that provides intense industry exposure and hands-on training.  

With the right skills and a strategic approach, data science can help you achieve substantial salary growth and long-term career success.

[eagletflysolutions]

Best Data Science Course in Laxmi Nagar

Data science is an interdisciplinary and emerging field. It combines mathematics and computing to analyse large and complex data sets. Our degree will give you the skills to turn data into meaningful outcomes. You'll learn to use your analytical and computational skills to interpret, clean, and visualise data confidently. You'll graduate with expertise in the most relevant and innovative data science topics. You'll learn and work alongside leading practitioners in data science - data science and data analytics course.

This program introduces students to different techniques and tools for handling, managing, analyzing, and interpreting data. It is designed for working professionals who are interested in gaining hands-on experience working with data and analyzing it. This program primarily focuses on data management and analysis with introductions to tools such as Oracle SQL, Tableau, Python etc. After completing the program, the students will have a solid foundation for applying advanced statistics and quantitative methods to make informed, effective decisions - Best data science institute in delhi.

The program has also successfully made several collaborations with different institutions and companies that can benefit from it. Students who opt for this program have the option to transfer credits for Master’s programs with top-ranked universities and gain lateral entry int sem directly. Overall, this is an ideal data science course for beginners as the instructors let you begin with the basics and build up as you progress. When embarking on your data science education journey, evaluate your skill levels, career goals and timelines to pick courses aligning to your learning needs. You’ll also be able to use SQL effectively for targeted analysis by interpreting the structure, meaning, and relationships within the data.

You will engage with a variety of learning materials, such as videos, assessments, and hands-on labs, to familiarize yourself with the tools and analytical skills needed to work with data. Attendance is not just about the student’s willingness to learn but is also indicative of how the program is conducted to keep the student’s attention. For more information, please visit our site https://eagletflysolutions.com/ 

[scmsnoida]

Top Career Paths After a BBA in Business Analytics

Companies depend on data-driven decision-making to remain competitive in the modern digital era. Business analytics is revolutionising industries worldwide, from forecasting consumer actions to maximising investment returns. A BBA in Business Analytics prepares students to read data, identify patterns, and offer actionable insights that help businesses thrive.

At a BBA college in Noida, students get practical data analysis, visualisation, and strategic decision-making training, equipping them for high-growth professions. If you want to know what opportunities lie after this degree, here are your best career choices.

1. Data Analyst

A Data Analyst translates complex data sets to make informed decisions. The finance and e-commerce sectors depend on data analysts to determine trends. They enhance efficiency and provide a better customer experience.

Real-World Example: An SCMS Noida alumnus joined a fintech company, applying data analytics to analyse customer spending patterns and enhance financial products.

2. Business Intelligence Analyst

A Business Intelligence (BI) Analyst converts raw data into insights using Power BI and Tableau software. This is the most important job in companies that want to optimise operations and boost profitability.

Industry Impact: A retail company in Noida maximised its sales strategy using BI dashboards, generating revenue growth of 20%.

3. Marketing Analyst

Marketing Analysts research consumer behaviour, campaign performance, and market trends. As digital marketing takes centre stage, companies require specialists who can optimise marketing strategies and yield high ROI.

Internship Highlight: A student from a BBA college in Noida interned with a digital marketing company, applying analytics to drive SEO rankings and ad conversions.

4. Financial Analyst

Financial Analysts translate market trends, estimate risks, and inform investment strategies. They function in banks, investment banks, and corporate financial departments to increase profitability while decreasing risk.

Success Story: Today, an SCMS Noida graduate assists a stock brokerage firm in optimising investment portfolios through predictive analytics.

5. Operations Analyst

Operations Analysts enhance supply chain effectiveness and recognise bottlenecks in business procedures. The function is highly valued in e-commerce and manufacturing businesses.

Case Study: An Operations Analyst helped an e-commerce company based in Noida minimise delivery times by 30%. 

6. HR Analytics Specialist

HR Analytics Specialists examine employees' data for better recruitment, retention, and workplace culture. Most IT companies and MNCs hire HR analysts to strengthen data-driven teams.

‍Intern in the Spotlight: A student of SCMS Noida interned at a technology firm, assisting them in optimising workforce planning through analytics.

Conclusion

The demand for Business Analytics professionals is skyrocketing across industries. Whether you aim to join a top MNC, work in finance, or start your own business, a BBA in Business Analytics from SCMS Noida gives you the perfect launchpad for success.

If you are ready to build a future-proof career, now is the time to embrace the power of data!

[datavisualisationservices]

Choosing the Right Data Visualisation Solution for Your Business Needs

Introduction

Businesses rely heavily on data visualisation solutions to extract meaningful insights and facilitate informed decision-making in the modern data-driven world. However, selecting the right solution can be overwhelming with the vast array of data visualisation tools available. A well-chosen visualisation tool can enhance business efficiency, improve collaboration, and provide deeper insights.

Understanding Data Visualisation Solutions

Data visualisation solutions transform raw data into graphical representations such as charts, graphs, dashboards, and maps. These solutions help businesses interpret complex data patterns, trends, and correlations more effectively. Choosing the right tool requires a thorough understanding of business objectives, data complexity, and user requirements.

Key Considerations When Choosing a Data Visualisation Solution

1. Business Objectives and Use Cases

Before selecting a tool, businesses must define their primary use cases. Are they looking to improve internal reporting, track key performance indicators (KPIs), or create real-time interactive dashboards? Understanding these objectives will narrow down suitable options.

2. Ease of Use and User Experience

A data visualisation solution should be user-friendly, catering to both technical and non-technical users. A tool with an intuitive interface and drag-and-drop functionalities can empower business users to generate insights without extensive technical expertise.

3. Integration with Existing Systems

The chosen tool must integrate seamlessly with existing databases, business intelligence (BI) platforms, and cloud services. Compatibility with data sources such as SQL databases, spreadsheets, and cloud applications ensures smooth data flow.

4. Customisation and Scalability

Businesses should consider whether the tool can be customised to meet specific needs and scale as the company grows. A scalable solution will support increasing data volumes and more complex analytics over time.

5. Advanced Analytical Capabilities

Some businesses require more than basic visualisation; they need predictive analytics, artificial intelligence (AI)-driven insights, and machine learning capabilities. Selecting a tool that provides these features can give businesses a competitive edge.

6. Collaboration and Sharing Features

For organisations with multiple teams, a tool that allows collaborative data exploration, report sharing, and real-time updates is essential. Cloud-based solutions enhance teamwork and remote access.

7. Security and Compliance

Data security is a top priority. Businesses must evaluate whether the solution meets compliance regulations (such as GDPR or HIPAA) and offers encryption, role-based access control, and secure authentication methods.

8. Cost and ROI Consideration

While budget constraints are important, businesses should weigh the cost against potential benefits. A higher-priced tool with robust features may offer greater long-term value compared to a cheaper, limited-scope solution.

Popular Data Visualisation Tools in the Market

Several tools cater to different business needs. Some of the most popular include:

Tableau – Best for advanced analytics and interactive dashboards.

Power BI – Ideal for Microsoft ecosystem users and enterprise-level reporting.

Google Data Studio – Great for free, cloud-based reporting and collaboration.

D3.js – Suitable for developers who need custom visualisation capabilities.

Looker – Best for integrating BI and data analytics into workflows.

Conclusion

Choosing the right data visualisation solution requires careful evaluation of business needs, technical requirements, and budget. By considering factors such as ease of use, scalability, integration, and security, businesses can select a tool that maximises the value of their data. Investing in the right data visualisation solution empowers organisations to turn raw data into actionable insights, driving business growth and success.

[cavillionlearning]

Why Learn Tableau? Here are 5 powerful reasons to get started with this industry-leading tool

1. Industry-Leading Visualization: Transform raw data into stunning visuals!

2. High Demand in Data Analytics: Tableau skills are highly valued in today’s job market.

3. Actionable Insights in Minutes: Make data-driven decisions faster.

4. User-Friendly Interface: Easy to learn, even for beginners.

5. Boost Your Career: Stand out in data roles and advance your career! Want to take your skills to the next level?

Join our 1-day Tableau Bootcamp on 2nd November (Online)!

[excelrsolutionshyderabad]

Data Analyst Course and Storytelling: Creating Impactful Dashboards and Charts Using Tools Like Tableau and Power BI

In the modern data-driven world, raw data is only as valuable as the insights derived from it. For businesses, conveying these insights in an impactful and comprehensible way is critical for decision-making. This is where the art of storytelling in data analysis comes into play. A dedicated module on data visualisation and storytelling in a Data Analyst Course in Nagpur equips professionals to create impactful dashboards and charts using industry-leading tools like Tableau and Power BI.

The Role of Storytelling in Data Analysis

Storytelling in data analysis involves transforming complex datasets into visually compelling narratives that resonate with stakeholders. It bridges the gap that creeps in between data insights and actionable business strategies. Key components of effective data storytelling include:

Clarity: Simplifying complex information for easy comprehension.

Context: Providing relevant background to make data meaningful.

Engagement: Using visuals to capture and hold attention.

Actionability: Delivering insights that lead to informed decisions.

Why Focus on Dashboards and Charts?

Dashboards and charts serve as the backbone of data storytelling. They provide an interactive and visual medium to:

Monitor key performance indicators (KPIs).

Track trends and patterns over time.

Highlight anomalies and areas requiring attention.

Support data-driven decision-making with clarity and precision.

Key Features of Tableau and Power BI

Tableau:

Renowned for its user-friendly interface and powerful visualisation capabilities.

Allows integration with multiple sources of data for comprehensive analysis.

Offers advanced features like drag-and-drop functionality, real-time data updates, and storytelling dashboards.

Supports interactive visualisations like heatmaps, treemaps, and scatter plots.

Power BI:

A robust Microsoft tool that integrates seamlessly with Office 365 and other Microsoft products.

Provides AI-driven insights and natural language querying.

Offers a wide range of visual templates and customisation options.

Ideal for creating enterprise-grade reports and dashboards.

Course Highlights: Mastering Visualisation Tools

A Data Analyst Course focusing on storytelling and visualisation covers the following key areas:

Data Preparation and Cleaning:

Importing, cleaning, and organising datasets for visualisation.

Handling large and disparate data sources.

Designing Dashboards:

Principles of effective dashboard design: layout, colour theory, and usability.

Building interactive and dynamic dashboards in Tableau and Power BI.

Charting Techniques:

Selecting the right chart type for the data and audience.

Creating advanced visualisations like histograms, box plots, and waterfall charts.

Storytelling Frameworks:

Structuring narratives around visualisations.

Using annotations, highlights, and sequences to guide the audience.

Real-World Projects:

Hands-on experience with industry-relevant datasets.

Creating end-to-end dashboards addressing business scenarios.

Benefits of Mastering Data Storytelling

Professionals trained in data storytelling with tools like Tableau and Power BI can:

Communicate insights effectively and efficiently to both technical and non-technical audiences.

Drive strategic decisions with data-backed narratives.

Enhance their employability in industries prioritising data-driven approaches.

Build visually engaging reports that foster collaboration and understanding.

Conclusion

A Data Analyst Course in Nagpur emphasising storytelling and visualisation is essential for anyone aiming to excel in today’s data-centric roles. By mastering tools like Tableau and Power BI, participants can create dashboards and charts that not only inform but inspire action. This skillset ensures that data analysis evolves from mere number crunching to impactful decision-making support.

[heathersmithau]

Accounting Bingo 2025

🎙️ Welcome to the Accounting Apps podcast, where we spotlight trends and tools shaping the world of accounting. I'm Heather Smith, and today we’re playing a little game of Accounting Bingo for 2025! What's on the bingo card for the year ahead? We’re talking about technology, tools, and trends that are transforming our profession. Let’s dive in! 🎙️

Subscribe to the Accounting Apps newsletter here http://AccountingApps.io

This is the ChatGPT podcast script I used for the episode

Square 1: AI-Driven Automation 🤖 It’s no surprise that AI is at the top of our bingo card.

In 2025, AI is automating repetitive tasks, analysing vast amounts of data, and even predicting trends. Whether it's categorising transactions or providing forecasting insights, AI tools are making accountants' lives easier.

Brand Watch: Xero’s AI-powered bank reconciliation and QuickBooks’ Smart Suggestions are leading the charge.

    Square 2: ESG Reporting Tools 🌱 Environmental, Social, and Governance (ESG) is no longer optional.

With mandatory ESG reporting becoming standard, accountants are helping clients track their sustainability metrics alongside financial ones.

Brand Watch: Spotlight Sustain: Measure and enhance the positive impact that your organisation or clients can create. SAP and Oracle are embedding ESG tools right into their platforms, making it simpler to comply with new regulations.

    Square 3: Cloud-Based Collaboration ☁️ Cloud-first is the only way forward.

Accountants are embracing platforms that allow teams and clients to collaborate in real-time, from anywhere in the world. Cloud-based solutions have become essential for remote and hybrid work.

Brand Watch: Xero, MYOB, and QuickBooks Online are household names, while Karbon is adding powerful collaboration features for practice management.

    Square 4: Data Analytics and Visualisation 📊 Seeing is believing – and understanding.

Advanced analytics tools are helping accountants go beyond numbers to tell compelling stories with data. Visualisation tools are bringing balance sheets and profit-and-loss statements to life.

Brand Watch: Power BI, Fathom, and Tableau are must-haves for visualising financial insights.

    Square 5: Enhanced Cybersecurity 🔒 Security is non-negotiable.

With the rise of cyberattacks, protecting client data is critical. Accountants need robust cybersecurity measures built into their workflows.

Brand Watch: Platforms like Practice Protect and 1Password are safeguarding sensitive financial information.

    Square 6: Advisory 💼 Advisory is the future.

Accountants are evolving into strategic advisors, helping clients make data-driven decisions to grow their businesses. Offering more personalised services is the new normal.

Brand Watch: Clarity HQ https://clarity-hq.com/ The Gap https://www.thegaphq.com/ 

    Square 7: Remote Work Technologies 🏠 Work from anywhere, but stay connected.

Accountants are relying on tools that keep their teams productive and clients engaged, no matter where they’re working from.

Brand Watch: Microsoft Teams and Zoom remain essentials, while Slack adds another layer of real-time communication.

    Square 8: Automation for Compliance 📜 Stay compliant without the headache.

With ever-changing regulations, automation tools are stepping up to handle compliance tasks. From tax filings to payroll, automation reduces errors and saves time.

Brand Watch: XBert and ATO-certified tools like BAS Agent Portal integrations are a hit in Australia.

    Square 9: Simplified Payments 💳 Get paid faster and easier.

Streamlined payment solutions are helping accountants and their clients manage cash flow more effectively.

Brand Watch: Ignition Solo is a new offering for automated agreements and payments. 

    Square 10: Sustainability in Practice 🌍 Greener practices for a better future.

Beyond ESG reporting, accountants are looking inward to adopt sustainable practices in their own businesses.

Brand Watch: Platforms like Dext are enabling paperless workflows, contributing to a greener planet.

    Conclusion

🎙️ That’s our bingo card for 2025! Which trends are you already embracing, and which ones are still on your wishlist? The world of accounting is evolving rapidly, and staying ahead of these trends will help you thrive in the year ahead. Thanks for tuning in to the Accounting Apps podcast. Until next time, keep innovating! 🎙️

Subscribe to the Accounting Apps newsletter here http://AccountingApps.io

Contact details:

Accounting Apps newsletter: http://HeatherSmithAU.COM

Accounting Apps Mastermind: https://www.facebook.com/groups/XeroMasterMind 

LinkedIn: https://www.linkedin.com/in/HeatherSmithAU/ 

YouTube Channel: https://www.youtube.com/ANISEConsulting 

X: https://twitter.com/HeatherSmithAU

Cloud Stories w. @HeatherSmithAU

[kanikarawat758]

Free Data Science Courses to Build Your Career Skills

Introduction

Data science is transforming industries, making it one of the most in-demand skills in today's job market. With the global data science platform market projected to grow from $95.3 billion in 2021 to $322.9 billion by 2026 at a staggering CAGR of 27.7%, professionals with data expertise are in high demand. 

Free data science courses provide an excellent opportunity to upskill without financial barriers. They enable you to learn data science for free, covering everything from basic concepts to advanced techniques. This blog highlights top free resources, helping you kickstart or advance your career in this rapidly growing field.

Top Free Data Science Courses

Data Science is evolving rapidly, and finding quality resources for learning without paying is now easier than ever. Whether you’re new to Data Science or looking to expand your knowledge in specialised areas like Machine Learning or Data Visualisation, free online courses offer a fantastic opportunity to learn at your own pace. 

Here’s a comprehensive guide to the top free Data Science courses available. Each course provides a unique focus, giving you options to build your Data Science skills effectively and affordably.

Applied Data Science by Future Learn

Future Learn’s Applied Data Science course collaborates with Coventry University, the Institute of Coding, and Birkbeck University to introduce students to the practical aspects of Data Science. This beginner-friendly course emphasises Data Visualisation, Machine Learning applications, and clustering techniques.

Key Features

User-Friendly Platform: Future Learn offers an intuitive experience with flexible schedules and engaging video-based learning.

Focus on Applied Data Science: Practical examples help users apply Data Science methods to real-world business cases.

Self-paced Learning: Students can start anytime and learn at their speed.

Certificate Option: Obtain a certificate for an additional 6,222 ₹.

Accessible Topics: Covers geolocation data, feature extraction, and introductory Machine Learning.

Data Science Professional Certificate by IBM on Coursera

The IBM Data Science Professional Certificate on Coursera offers an in-depth curriculum spanning nine courses. This specialisation takes about 11 months to complete. It includes a capstone project designed to simulate real-world data challenges, making it one of the most comprehensive free courses in Data Science.

Key Features

Nine-Course Structure: Covers everything from basic Data Science concepts to advanced SQL and Python.

Capstone Project: Provides a simulated real-world experience.

Certificate Upon Completion: Receive a shareable certificate on Coursera upon successful completion.

Excellent Instruction Quality: Taught by experienced IBM professionals.

Career-Boosting Potential: Many students use this course as a launchpad for Data Science careers.

Data Science Course by Pickl.AI

Pickl.AI’s Data Science Course is structured into 11 modules, covering everything from SQL and Tableau to Machine Learning techniques. With hands-on exercises and real-world case studies, this course is designed for beginners and professionals looking to advance in Data Science.

Key Features

Extensive Modules: Includes 462 lessons on SQL, Python, Machine Learning, and more.

Real-Life Case Studies: Learn through practical examples and case studies.

Certification Available: Certification offered upon completion, enhancing employability.

Focus on Data Science Tools: Access high-demand tools like Tableau and Power BI.

Flexible Pace: Allows learners to move through modules at their own speed.

Introduction to Data Science by Alison

Alison’s Introduction to Data Science course is a quick, impactful introduction to core Data Science concepts. It’s highly rated among working professionals and provides insights into data structuring, Machine Learning basics, and essential Data Science processes.

Key Features

Quick Overview: Completes in 1.5 to 3 hours, ideal for busy professionals.

Beginner-Friendly: No prior knowledge is required, making it accessible to everyone.

Certification Included: Receive a certificate upon completion, adding value to resumes.

Focus on Practical Skills: Learn data extraction, modelling, and scientific methods.

User-Friendly Platform: Alison is known for its ease of use and career-focused course design.

Data Science and Machine Learning with Python by Skillshare

Skillshare’s Data Science and Machine Learning with Python course offers an immersive look into Python, regression models, and ensemble learning, with a two-week free trial for new users. Frank Kane, an expert with over nine years of experience at Amazon and IMDB, leads this course, making it an excellent option for in-depth Python training.

Key Features

Access with Free Trial: Skillshare’s two-week free trial allows full access to the course.

Professional Instructor: Frank Kane brings practical experience and industry insights.

In-Depth Python Training: Covers foundational Python skills and data manipulation.

Beginner-Friendly: No prior knowledge is needed to start.

10-Hour Format: Perfect balance of depth and accessibility, making it manageable for beginners.

Conclusion

Free data science courses provide an excellent pathway to upskilling and breaking financial barriers. With platforms like Future Learn, IBM, and Pickl.AI offering specialised modules, learners can grasp core concepts, explore advanced techniques, and boost their career potential. Start today and embrace the growing demand for data science skills in this dynamic, evolving industry.