Xano is an incredibly powerful backend-as-a-service (BaaS) platform that simplifies backend development by providing a robust and flexible infrastructure. In this blog, we'll cover some fundamental aspects of Xano, including its database, file storage, external database connection, deployment, notification integration, pricing, and server locations.

Database Used by XANO

Xano hosts your data on a PostgreSQL database, known as the most powerful open-source database in the world. This database offers the flexibility of a relational database and the capacity to handle the big data needs of a NoSQL solution. PostgreSQL’s reliability and performance make it an ideal choice for Xano.

File Storage in XANO

For performance reasons, Xano does not store actual files in the database. Instead, Xano stores references to the files for quick retrieval, utilizing Google Cloud Storage for media storage. This approach optimizes both bandwidth and performance capacity.

Content Upload Limitations:

• Most file types are allowed, except for executable files.
• File size limits are as follows:
  • 64MB on the Build plan
  • 128MB on the Launch plan
  • 2GB on the Scale plan

Connecting External Databases to XANO

Xano does not support the use of external databases. However, many users have successfully migrated their data from SQL databases to Xano’s database using the CSV import feature. This feature is limitless and can handle files of any size, making the migration process smooth and efficient.

Deployment of XANO

Xano takes care of monitoring and managing your DevOps, allowing you to focus on your business. Each instance is hosted on Google Cloud, provisioned with Docker, and orchestrated by Kubernetes to provide a stable and scalable environment. For users seeking more control, the Enterprise plan offers the ability to manage Xano on your own cloud and resources.

Notification Integration with XANO

Integrating notifications with Xano is straightforward with the help of a tutorial that demonstrates how to use Xano with Firebase and Flutterflow. You can follow this tutorial to set up notifications: How to integrate XANO + Firebase + Flutterflow.

Pricing for XANO

Xano offers a range of pricing plans to suit different needs. For detailed pricing information, you can visit Xano’s pricing page: Xano Pricing.

XANO Server Locations

To ensure optimized performance and data redundancy, Xano’s servers are strategically located around the world. The server locations include:

• Australia (Sydney)
• Brazil (São Paulo)
• Canada (Montréal)
• Germany (Frankfurt)
• India (Mumbai)
• Singapore
• UK (London)
• United States

These locations help provide robust and reliable service across different regions, catering to a global user base.

Conclusion

Xano is a powerful and flexible backend platform that simplifies backend development by leveraging PostgreSQL for data storage, Google Cloud Storage for media, and Kubernetes for deployment. Whether you need to migrate data from an external database, set up notifications, or choose a pricing plan, Xano provides the tools and support to help you succeed. With servers located worldwide, Xano ensures optimal performance and reliability for your applications.

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What is a Data Scientist?

A data scientist uses data to understand and explain the phenomena around them and helps organizations make better decisions. They are part mathematician, part computer scientist, and part trend-spotter. Straddling both the business and IT worlds, they are highly sought-after and well-paid. Who wouldn’t want to be one?

What Does a Data Scientist Do?

A data scientist’s primary responsibility is to extract meaningful information from data and analyze it. Typical job duties and responsibilities of a data scientist include:

• Designing data modeling strategies and suggesting economic modifications to existing methods and strategies.
• Building machine learning algorithms and data models to forecast outcomes.
• Continuously extracting massive volumes of structured data (using programming languages like SQL) as well as unstructured data (via APIs, web scraping, and surveys). Collaborating with various departments to solve business concerns via scientific tools.
• Cleaning data to remove irrelevant information and conducting exploratory data analysis to address missing data.

Data Analyst vs Data Scientist: What’s the Difference?

The work of data analysts and data scientists can seem similar—both find trends or patterns in data to help organizations make better decisions about operations. However, data scientists tend to have more responsibility and are generally considered more senior than data analysts.

• Data Analysts: Support teams with set goals, understanding business problems, identifying relevant datasets, cleaning, blending, and analyzing data to help businesses make informed decisions.
• Data Scientists: Form their own questions about data, develop models using machine learning, and incorporate advanced programming to find and analyze data. Their responsibilities include developing and implementing predictive models and algorithms to solve strategic business problems.

Why Become a Data Scientist in India?

• Average Salary: ₹956K/Yr (Source: Glassdoor)
• Demand Increase: 62% expected increase (Source: TOI)
• Opportunities: Internet growth leads to more data, creating opportunities in data science.
• Top Companies: Google, Microsoft, Flipkart, and Amazon are constantly searching for talented data scientists.

A Roadmap to Becoming a Data Scientist

There hasn't been a better time to get into data science and build your career. Here's a step-by-step roadmap to becoming a data scientist in 2023:

1. Mathematics & Statistics

Understanding mathematics and statistics is fundamental before diving into programming.

• Learn basic statistics from resources like Hines (PDF available online).
• Understand concepts like dy/dx, optimization, and gradient descent. Use playlists and tutorials to grasp these basics.
• Plot simple functions in Excel to practice.
• Focus on probability distributions, especially normal distribution.

2. Programming

Python is recommended due to its popularity and widespread use in data science.

• Learn Python basics.
• Explore libraries like NumPy (CodeWithHarry has great videos).
• Learn Pandas for data manipulation.
• Use Matplotlib/Seaborn for data visualization.
• Understand time complexity of algorithms and database storage.

3. Big Data and External Data Visualization Tools (Optional)

While Python can handle data visualization and big data, external tools can be more efficient for specific tasks.

• Learn tools like Tableau, Excel (& VBA), Hadoop, and AWS offerings.
• Note that mastering these tools might take time.

4. Machine Learning and Deep Learning

After mastering data wrangling with Python, focus on machine learning concepts.

• Start with Google's free machine learning course.
• Learn Scikit-Learn (Sklearn).
• Build neural networks with TensorFlow.
• Explore TensorFlow Hub and TensorBoard.
• Consider free courses from Kaggle and Coursera.

5. Linux & Version Control

Managing and collaborating on software projects is essential.

• Learn Linux basics.
• Master Git for version control.
• Follow papers with code, GitHub trending repositories, and data science news.
• Learn to scrape data from websites.

Other Points to Remember

• Computer Science Degree: Helpful but not essential.
• Domain-Specific Knowledge: Increases job prospects.
• Communication Skills: Good communication and spoken English are valuable.
• Staying Competitive: Staying ahead of the competition is crucial.

I wish you all the best in learning data science. I hope this information helps you on your journey to becoming a data scientist.

Difference between Universal Analytics and GA4

Universal Analytics (UA) has been widely used by many websites for tracking and analyzing data. However, starting from July 2023, GA4 (Google Analytics 4) is mandatory. GA4 offers enhanced tracking capabilities and insights compared to Universal Analytics.

How to Create an Account on Google Analytics

Step 1: Log in to Gmail

Ensure you are logged into your Gmail account before starting the setup process.

Step 2: Start Measuring

• Click on the "Start Measuring" button to begin the setup.

Account Setup

1. Account Name: You can choose any name you want here; it doesn't have to match your Gmail or website name.
2. Data Sharing Settings: Select the checkboxes according to your preferences.

Property Setup

1. Property Name: Enter the name of your website.
2. Reporting Time Zone: Set this to India (or your local time zone).
3. Currency: Choose the currency you prefer (e.g., USD or INR).

Advanced Options (Optional):

• By default, your account will be created on GA4. If you click on "Show Advanced Options," you can choose to create a Universal Analytics property or both GA4 and Universal Analytics properties.

About Your Business:

• Select the options that best describe your business.

Click "Create" to complete the setup.

Step 3: Admin Setup

1. In the Admin panel, you can find your tracking ID.
2. Account setup and property creation alone are not enough for website tracking.

Adding the HTML Tag:

1. Go to the Admin panel. If it doesn't open directly, you can access it from the left menu.
2. In the Admin panel, navigate to your account and property settings.
3. Click on "Tracking Info" -> "Tracking Code."
4. Copy the HTML tag provided.

Integrating the HTML Tag:

1. Add the HTML tag to the head section of your website's code.
2. Alternatively, you can use Google Tag Manager to manage the tag.

Conclusion

By following these steps, you can set up Google Analytics for your website and start tracking data efficiently. The transition to GA4 provides better analytics capabilities, ensuring you gain more insights into your website's performance.

What does PEEL stand for?

PEEL stands for:

• P -> Point
• E -> Explain or Evidence
• E -> Evaluate or Explain
• L -> Link

What is the PEEL Method?

The PEEL method is a structured approach that helps you write effective blogs or essays. It guides you on how to construct each paragraph so that your writing is clear, concise, and engaging. By following the PEEL method, you ensure that your ideas are well-organized and your arguments are well-supported.

Components of the PEEL Method

1. Point
2. This is where you introduce the main point of the paragraph. Clearly state the main idea you are going to discuss. Each paragraph should focus on a single point to maintain clarity and coherence.
3. Explain or Evidence
4. Here, you expand on your point. Provide explanations, evidence, research, references, examples, or quotes to support your point. Analyze and comment on the evidence, explaining how it supports your argument within the context of your essay.
5. Evaluate or Explain
6. Further evaluate the content and analyze the example you provided. Explain why the evidence works within the context of your essay question and argument. This step deepens the analysis and reinforces the significance of your point.
7. Link
8. Connect the current paragraph to the next one, and link back to the main idea of your essay. This ensures a smooth transition between paragraphs and reinforces your overall argument.

Checklist for PEEL Essay Writing

1. Paragraph Planning
   • Plan what will go into each paragraph.
   • Ensure your paragraph is impressive and meaningful.
2. Topic Sentence Writing
   • Write a topic sentence that expresses the main point of the paragraph.
   • Ensure the topic sentence is clear, strong, and concise.
3. Appropriate Examples Included
   • Support your point with evidence and examples.
   • Include facts, statistics, research findings, or quotes from credible sources.
4. Linking All Statements
   • Reinforce your original point or transition to the next paragraph.
   • Ensure connections are clean and neat.
5. Proofreading the Paragraph
   • Check for grammar, spelling, and punctuation errors.
   • Ensure the paragraph is error-free and plagiarism-free.

Conclusion

1. What is the PEEL Method?
   • A structured approach to writing effective essays and blogs.
2. 4 Steps to PEEL Writing Method
   • Point, Explain/Evidence, Evaluate/Explain, Link.
3. Checklist to PEEL Essay Writing
   • Plan paragraphs, write clear topic sentences, include appropriate examples, link statements, and proofread.

Using the PEEL method helps ensure that your writing is structured, clear, and compelling, making it easier for readers to follow and understand your arguments.

On 17th Dec 2022, a one to one meeting was held with Mr Sanjeev (CEO of ProDT). It was nice to meet with such a humble and motivated person who did a lot of things in his life and motivated others to do such things. Here are some points that we discuss:-

Four pillars of ProDT

First pillar is "Employees" 

All they want to a fully motivated employee. An employee who is motivated to do new things accepting challenges. For that an employee have to do one thing "to be healthy". Employees have to give certainty to the client and that is only possible if you are fit by mind and body. And if you are not feeling well with the technology you are working with just tell your reporting person they will definitely swtich you to what you love. So you will work with 100% of motivation. 

Second pillar is "Mee time" 

Mee time is the time for employees when they learn something for their career growth. It could be anything which an employee feels as a barrier in their career like a new technology, communication skill or any other. And how to gain 100% of what you learn is by writing a blog or making a video blog. If you read something you will forget it in a certain time but if you make a blog then you get 100% of it because while writing you are more active then reading. These blogs are also helpful for any employee to get a new job by this blog any other employer can see your expertise. 

Third pillar is "Financial planning" 

Most amazing not only Prodt has a financial plan in fact they teach employees to make a financial plan track your financial records. Many people are not aware of financial planning. People only know that they have only one option to go to the bank and deposit money there. But if we deposit ₹1000 per month for 30 years in a bank, after 30 years our money would be around 3 lac to 4 lac. But if we invest them in any mutual fund, stock market or any other business then we expect after 30 years our money would be around 20 lac to 30 lac or more than this. We all have to practice some atomic habits like if we exercise in our 20s we will get benefit in 50s or 60s. Like exercise we have to practice for financial planning. 

Fourth pillar is "Social life" 

At a certain age of life we all have to help our society like Pdodt CEO does by mentoring their employees by these 4 pillars help and motivate their employees to go through these 4 pillars.