Union Budget 2024-25 – All You Need to Know

The Union Budget is a yearly financial plan presented by the Finance Minister of India for the development of the country. For the year 2024-25, Finance Minister Nirmala Sitharaman announced important changes to simplify the tax system and boost economic growth. With a focus on job creation and youth skilling, ‘EMPLOYMENT’ was the theme of Union Budget 2024-25.

Here, each letter represents a key focus area: Employment, MSMEs, Productivity, Land, Opportunity, Youth, Middle Class, Energy Security, New Generation Reforms, and Technology. These ten priorities outline the government’s strategy for economic growth and development.

Budget 2024 Key Highlights

Below are the major announcements from the Union Budget 2024:

• Income Tax Changes: Introduction of new income tax slabs and an increase in the standard deduction.
• Social Security: Enhancements to the National Pension Scheme (NPS) deductions.
• Sectoral Focus: Emphasis on agriculture, MSMEs, and employment generation.

Taxation Changes

The budget introduces several changes to the income tax regime. So, here are the revised tax slabs under the New Tax Regime:

New Tax Slabs

• Up to ₹3 lakh: 0%
• ₹3 lakh to ₹7 lakh: 5%
• ₹7 lakh to ₹10 lakh: 10%
• ₹10 lakh to ₹12 lakh: 15%
• ₹12 lakh to ₹15 lakh: 20%
• Above ₹15 lakh: 30%

With this new regime, salaried employees can save up to ₹17,500/- in income tax.

• Income Tax Standard Deduction: Increased from ₹50,000 to ₹75,000 to provide more relief to salaried employees.
• Long Term Capital Gains Tax: LTCG gains tax hiked from 10% to 12.5%.

Social Security and Employment Benefits

The budget also introduces several measures to enhance social security and employment:

• Increased NPS Deductions: Employers’ contributions to NPS have been increased from 10% to 14% of the employee’s salary.
• One-Month Wage for New Entrants: The government will provide a one-month wage to all new employees in the formal sector in 3 instalments up to ₹15,000. This would directly be transferred as part of their provident fund contribution.
• Family Pension Deduction: The deduction on family pensions has been increased from ₹15,000 to ₹25,000, thereby, providing better financial stability to pensioners.

Impact On Major Sectors and Funds Allocation

Different sectors are set to benefit from various budget allocations:

• Agriculture and Allied Sectors: ₹1.52 lakh crores have been allocated to enhance strength and productivity in the agricultural sector.
• Education: For education and employment, a total of ₹1.48 lakh crores has been allocated.
• Healthcare: Funds of approximately ₹90,958 crores are allocated for building healthcare facilities to improve public services.
• Infrastructure: To maintain and increase infrastructural development, ₹11.11 lakh crores have been allocated in the Union Budget 2024.
• Urban Development: For upgrading urban infrastructure, ₹82,575 crores have been allocated by the government.
• Technology and Innovation: A total of ₹21,936 crores has been allocated to the Ministry of Electronics and Information Technology to support startups and technology companies.

Revenue and Expenditure

The budget outlines the government’s revenue and expenditure plans:

• Revenue Forgone: Approximately ₹37,000 crore in revenue will be forgone due to the new tax changes, with an additional ₹30,000 crore to be mobilised.
• Expenditure Plans: The government is set to spend ₹48,20,512 crore in 2024-25, which is 8.5% more than the actual expenditure in 2023-24. The major expenditure areas include agriculture, infrastructure, social welfare programs, and employment schemes.

Economic Projections and Targets

• GDP Growth: The budget highlights the expectation for continued strong economic performance.
• Fiscal Deficit: A target set at 4.9% for the fiscal deficit with plans to reduce it to 4.5%.

MSMEs and Employment Generation

The budget also looks forward to supporting Micro, Small, and Medium Enterprises (MSMEs) and generating employment. As a result, it doubles the Mudra loan limits to ₹20 lakh and implements a digital credit assessment model to nurture growth in the MSME sector.

Impact On Gold Price

As per the Budget 2024, the import duties on gold have been reduced from 15% to 6%. This custom duties cut will reduce the taxes on gold from 18.5% to 9%, eventually, reducing the price of gold.

Conclusion

So, this sums up the basics of the Budget 2024 key updates.

Now, if you are looking for instant personal loan to manage your expenses, the  app is a great choice. It offers quick and easy personal loans with minimal documentation and is perfect for emergencies, home renovations, or other personal expenses.

Moreover, with the reduction in import duties on gold, you can consider investing in digital gold with and have a hedge against inflation. Download the app now!

 

How to Get a Personal Loan Without ITR?

Do not have an income tax return (ITR) but are looking for a personal loan? Worry not! Though many lenders ask for an ITR to check your income and ensure you can repay the loan, there are ways to get an instant personal loan even if you do not have one. In this brief guide, let’s dive deeper into the topic and understand how to get a personal loan without ITR. You would also learn the importance of ITR, tips on getting an instant loan without ITR, documents required for a personal loan without ITR, and more.

What is an ITR?

An Income Tax Return (ITR) is a form that you file with the government to report your income for the year. It is a way to show how much money you earned and whether you paid the right amount of taxes. Personal loans on ITR are quite common as lenders often ask for ITR to confirm if you have a steady income and can repay a loan.

Importance of ITR

ITR shows your income over the past financial year and hence, it is proof that you have a regular income. It makes it easier to get a loan, especially if you are asking for a large amount. Having an ITR would help you get lower interest rates as it shows you are a low-risk borrower. Filing ITR also allows you to claim tax deductions, and if you file it regularly, then it would boost your credit score.

Scenarios Where You Might Not Have an ITR

• Freelancers or small business owners may not file ITR if their income is below the taxable limit.
• If you just started working, you might not have filed an ITR yet.
• If you are currently not working, you might not have an ITR.
• Senior citizens living off their savings might not need to file an ITR.

Alternative Documents and Proofs to Secure a Personal Loan Without ITR

Here are the documents required for a personal loan without ITR:

• Bank statements for the past 6-12 months
• Recent pay slips from your job
• Form 16 from your employer
• GST returns for business owners
• Rental income proof
• Property documents, if you own a property
• Investment proof
• An excellent credit score

Types of Personal Loans Available Without ITR

• Secured loans where you provide something valuable like gold or property as security
• Instant personal loans from apps 
• Loans secured by your investments such as shares
• Loans based on your salary slips and bank statements
• Loans from Non-Banking Financial Companies
• Loans against salary account

Tips for Securing a Personal Loan Without ITR

• Always keep an excellent credit score
• Use bank statements, salary slips, or other documents to show income
• Offer something valuable as security can help you get a loan
• Choose the right lender like CASHe
• Keep your existing loans and debts manageable
• Start with a smaller loan amount, If it is your first time borrowing without ITR

Conclusion

This is how you can get a personal loan without ITR. Now, if you are looking for an instant personal loan without income proof and with competitive interest rates, then download the CASHe app. CASHe offers instant personal loans without ITR and provides a simple and fast way to apply for a loan with minimal paperwork. So, wait no further, and explore instant personal loan options today!

 

Documents required for quick loan

 We all hustle and work hard to keep pace with our lifestyle needs. It could be as simple as wanting to buy a car, renovating your house or wanting to backpack around Europe to experience the world. But not all these dreams may get covered by your salaries and there are times when we need urgent funds and this is when you might need some capital to take care of your expenses.

When you need quick funds, either for emergencies or last-minute expenses, a personal loan can be a lifesaver. However, before you can get approved for a quick loan, you need to ensure that you have all the necessary documents in order. In this guide, we will walk you through the essential documents required for quick loans and provide tips on how to prepare your documents efficiently.,/p>

Understanding Quick Loans

Quick loans are very much like personal loans but they can be availed in a shorter period and get capped around ₹3,00,000-5,00,000 by most financial institutions. They are a type of unsecured loan and are also known as instant loans in the market.

These loans are typically processed quickly, making them an ideal option for those in urgent need of money. To apply for a quick loan, you need to provide specific documents to the lender to support your loan application.

Essential Documents Required for Quick Loans

Like instant personal loans, quick loans also need mandatory submission of certain documents that will help the financial institution gauge your capacity to repay your loans and understand your overall profile. You will have to provide the following documents to be eligible for a quick loan:

Identification Proof: You will need to provide a copy of your Aadhaar card, passport, driving licence, or voter ID card as proof of your identity.

Address Proof: Documents such as utility bills, rental agreement, or Aadhaar card can be submitted to verify your residential address.

Income Proof: Bank statements, salary slips, income tax returns, or Form 16 can serve as proof of your income and repayment capacity.

Employment Proof: If you are a salaried individual, you may need to provide your employment offer letter, employee ID card, or appointment letter from your employer.

Business Proof (for self-employed individuals): If you are self-employed, documents such as a business registration certificate, GST certificate, or partnership deed may be required.

Credit Score: While not a document, your credit score plays a crucial role in determining your loan eligibility. Make sure to have a good credit score before applying for a quick loan.

How to Prepare Your Documents

Organize Your Documents: Create a checklist of all the required documents and ensure that you have them handy before applying for a quick loan.

Verify Document Validity: Check the validity of your identification and address proofs to ensure that they are up to date.

Maintain Clarity: Ensure that all documents are legible and free of any errors or alterations.

Seek Professional Help: If you are unsure about any document requirements, consider seeking assistance from a financial advisor or loan officer.

Conclusion

The idea of quick loans is to get funds on an immediate basis and if you provide all the documents on time, your loan can get sanctioned within 24 hours.

If you are looking for Instant personal loans up to ₹3,00,000 then go for CASHe because their loan disbursal process gets done within 15-20 minutes. There are no restrictions on the usage of the funds, the disbursal is quick and you get flexible loan tenures that are aligned with your repayment capacity.

Cloud Integration and Hybrid Data Solutions

 Cloud integration and hybrid data solutions involve combining on-premises infrastructure with cloud services to create flexible, scalable, and efficient data environments. This approach allows organizations to leverage the strengths of both local (on-premises) and cloud-based systems, enhancing performance, availability, and data management capabilities.

Here’s a deeper dive into Cloud Integration and Hybrid Data Solutions:

1. Hybrid Cloud Architecture

A hybrid cloud architecture combines private (on-premises) and public cloud environments. It allows data and applications to move between these environments, enabling:

• Flexibility: Workloads can be managed dynamically across on-premises and cloud environments based on performance, cost, or security needs.
• Cost Efficiency: You can keep sensitive or high-priority data on-premises while using the cloud for scalability and cost-effective storage.
• Disaster Recovery & High Availability: Data can be replicated or backed up in the cloud, ensuring business continuity in case of an on-premises failure.

2. Data Integration Strategies

Organizations can integrate data from multiple sources (on-premises, cloud databases, applications, IoT devices, etc.) to create a unified data platform. Key methods include:

• ETL/ELT: Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines move data between sources. ELT is more cloud-friendly as transformations occur after the data is loaded.
• Data Replication: Continuous replication of on-premises data to the cloud ensures data synchronization, providing low-latency access across environments.
• APIs: APIs connect various services, allowing applications in different environments to communicate seamlessly.

3. Cloud Data Services

Cloud platforms like Microsoft Azure, Amazon Web Services (AWS), and Google Cloud offer robust data solutions:

• Azure Synapse Analytics: Combines big data and data warehousing, offering real-time analytics over large datasets, whether stored on-premises or in the cloud.
• AWS Glue: Serverless data integration service that makes it easy to prepare data for analytics by combining data from various sources.
• Google BigQuery: Serverless data warehouse with built-in machine learning, designed for handling vast amounts of data across hybrid environments.

4. Multi-Cloud Strategy

Some organizations adopt a multi-cloud approach, using services from more than one cloud provider to avoid vendor lock-in, optimize costs, and improve redundancy. A well-executed multi-cloud strategy offers:

• Interoperability: Data and services work seamlessly across different cloud providers.
• Data Portability: Simplified movement of workloads between different cloud environments.
• Compliance & Regulation: Certain clouds may be chosen for specific workloads based on regional compliance or data residency requirements.

5. Edge Computing

Edge computing complements cloud and hybrid models by processing data closer to its source (e.g., IoT devices or local servers). This reduces latency and bandwidth costs, especially when processing time-sensitive data.

• Hybrid Edge Architecture: Combines edge computing with cloud services, sending processed data to the cloud for storage or further analysis while keeping latency-critical operations local.
• Use Cases: Real-time monitoring, predictive maintenance, and industrial automation.

6. Data Virtualization

Data virtualization allows for real-time access and query capabilities across diverse data sources without physically moving data. This reduces complexity in hybrid cloud scenarios, providing:

• Unified Data View: Access and manipulate data from multiple sources (cloud, on-premises, external) without duplication.
• Real-Time Analytics: Execute analytics directly on distributed datasets without the need for extensive ETL processes.

7. Security and Governance in Hybrid Solutions

Security remains a critical concern in hybrid solutions. Organizations need to implement:

• Data Encryption: Data must be encrypted both in transit (between environments) and at rest.
• Identity & Access Management (IAM): Ensure proper authentication and role-based access control (RBAC) for users across both cloud and on-premises environments.
• Compliance: Hybrid solutions need to meet regulatory standards (e.g., GDPR, HIPAA), especially when moving sensitive data between environments.

8. Cloud-Native Technologies in Hybrid Solutions

• Containers & Kubernetes: Kubernetes orchestrates containers across hybrid cloud environments, enabling portability and consistency in application deployment.
• Serverless Functions: Services like AWS Lambda, Azure Functions, and Google Cloud Functions allow code to run without provisioning servers, providing scalable compute in hybrid setups.
• Microservices Architecture: Enables the development of applications as small, independently deployable services. Microservices work well in hybrid environments, allowing specific services to run in the cloud while others remain on-premises.

9. Benefits of Hybrid Data Solutions

• Scalability: Utilize the cloud to handle spikes in demand while maintaining core workloads on-premises.
• Cost Control: Manage expenses by leveraging cloud resources dynamically and reducing dependency on expensive hardware.
• Innovation & Agility: Experiment with new cloud services (like machine learning, AI, or advanced analytics) without disrupting core on-premises operations.
• Data Sovereignty: Maintain control over sensitive data by keeping it on-premises while using the cloud for less critical data or compute-heavy tasks.

10. Real-World Use Cases

• Healthcare: Hybrid solutions allow sensitive patient data to remain on-premises while analytics and machine learning run in the cloud.
• Financial Services: Banks use hybrid architectures to comply with regulations that mandate data residency while leveraging cloud platforms for AI-driven risk assessment or fraud detection.
• Manufacturing: Edge devices collect data on the factory floor, process it locally, and send summary data to the cloud for further analysis.

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By combining the strengths of on-premises systems and cloud platforms, cloud integration and hybrid data solutions offer businesses a path to scalable, secure, and cost-effective data management, enabling them to handle modern workloads and adapt to evolving technology landscapes.

Intelligent Query Processing (IQP)

 Intelligent Query Processing (IQP) is a suite of features introduced in SQL Server to optimize query performance with minimal changes to existing code. It is designed to automatically improve query performance by adapting to runtime conditions, reducing the need for manual query tuning. IQP is part of the broader Intelligent Database concept and includes several enhancements aimed at improving the performance of queries across various workloads.

Here are the key features of Intelligent Query Processing:

1. Batch Mode on Rowstore (SQL Server 2019)

• Previously, batch mode execution was only available for columnstore indexes. Now, SQL Server 2019 extends batch mode processing to rowstore tables, providing performance improvements for analytical queries on traditional rowstore tables.

2. Table Variable Deferred Compilation (SQL Server 2019)

• In prior versions, table variables were always assumed to have a single row at compile time, leading to suboptimal query plans when they contained more data. SQL Server 2019 defers the compilation of table variables until runtime when actual row counts are known, improving query performance.

3. Approximate Query Processing (SQL Server 2019)

• The APPROX_COUNT_DISTINCT function is introduced to provide faster approximate distinct count calculations for large datasets. This is useful in cases where exact precision is not required but performance is critical, such as in large analytical workloads.

4. Scalar UDF Inlining (SQL Server 2019)

• Scalar user-defined functions (UDFs) often caused performance bottlenecks because they were executed row-by-row. With inlining, SQL Server replaces the UDF calls with the function body, allowing the entire query to be optimized as a single unit and improving performance significantly.

5. Adaptive Joins (SQL Server 2017)

• SQL Server can now switch dynamically between Nested Loops and Hash Joins during query execution based on the actual row count. This helps optimize join performance in cases where cardinality estimates may be inaccurate.

6. Interleaved Execution for Multi-Statement Table-Valued Functions (SQL Server 2017)

• SQL Server can now defer execution of certain parts of the query plan involving multi-statement table-valued functions (MSTVF) until runtime when actual data sizes are known, leading to more accurate query plans and better performance.

7. Memory Grant Feedback (SQL Server 2017)

• SQL Server adjusts the memory allocated for query execution based on feedback from prior executions. If a query requests too much or too little memory, the system learns and adjusts the memory grant for future executions, reducing memory contention and improving performance.

8. Batch Mode Memory Grant Feedback (SQL Server 2019)

• Expanding on memory grant feedback, batch mode execution can now dynamically adjust memory grants, which is especially beneficial for large analytical queries, helping to avoid both under- and over-provisioning of memory.

9. Batch Mode Adaptive Joins (SQL Server 2019)

• Similar to adaptive joins, this feature extends adaptive behavior to batch mode, allowing the system to switch between join strategies at runtime based on data distribution and actual row counts.

10. Cardinality Estimation Feedback (SQL Server 2022)

• Introduced in SQL Server 2022, this feature helps improve the accuracy of query plans by updating cardinality estimates based on feedback from prior executions, optimizing for future runs.

11. Parameter Sensitivity Plan Optimization (SQL Server 2022)

• Parameter sensitivity issues can cause performance problems due to a single query plan being used for different parameter values. This feature addresses the problem by generating and storing multiple plans for a single query based on parameter values, improving query performance and reducing bottlenecks.

12. Degree of Parallelism (DOP) Feedback (SQL Server 2022)

• This feature optimizes the degree of parallelism used by queries, adjusting based on the actual runtime conditions. Over time, SQL Server learns and refines the parallelism strategy, improving the query's performance in future executions.

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These IQP features help SQL Server adapt to changing workloads and data distribution, reducing manual tuning effort while improving performance across OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) workloads. They contribute to more efficient query execution by learning from actual data and workload behavior.

Query Store Enhancements

 Query Store in SQL Server has received several enhancements in recent versions, making it even more powerful for performance monitoring and query tuning. Here are some of the key enhancements:

1. Query Store for Read-Only Replicas (SQL Server 2019)

• Query Store now supports capturing performance data on read-only replicas in Always On Availability Groups. This allows you to monitor and tune queries running on these replicas without impacting the primary.

2. Custom Capture Policies (SQL Server 2019)

• You can define custom capture policies for Query Store, which allows you to control which queries are captured based on factors such as execution frequency, resource consumption, or duration. This helps reduce overhead by ignoring less important queries.

3. Automatic Plan Correction (SQL Server 2017+)

• SQL Server can automatically detect and correct query performance regressions by reverting to an older query plan that is known to perform better. This is part of the Intelligent Query Processing (IQP) feature set.

4. Improved User Interface in SSMS

• The Query Store UI in SQL Server Management Studio (SSMS) has improved significantly, offering better visualization for comparing query performance over time, analyzing plan changes, and more.

5. Hybrid Workloads and Query Store for Cloud Environments

• Azure SQL Database and SQL Managed Instance also benefit from Query Store enhancements, such as the ability to monitor query performance across different environments (on-premises and cloud) and integrate with Azure monitoring tools.

6. Wait Statistics

• Query Store now includes wait statistics, which help you understand the causes of performance bottlenecks related to waits (e.g., I/O, locks, CPU). This provides better insight into the actual root causes of performance issues.

7. Aggregated Query Data

• Query Store now offers enhanced options for aggregating query data, making it easier to analyze query patterns and performance over longer periods of time without needing to focus on individual executions.

8. Query Store on a Per-Database Basis

• You can now enable or disable Query Store at the database level, providing more control over where Query Store is used and reducing unnecessary overhead in less critical databases.

These enhancements help developers and DBAs monitor, troubleshoot, and optimize query performance more efficiently across various environments.

10 What is the difference between decode and case?

 DECODE and CASE are both conditional expressions used in SQL to perform conditional logic within queries. However, they differ in syntax, functionality, and availability across different database systems. Here's a breakdown of the differences:

1. Syntax

• DECODE Syntax:

  
  
  DECODE(expression, search1, result1, search2, result2, ..., default)
  

  • expression: The value to be compared.
  • search: The value to compare against the expression.
  • result: The value to return if the search value matches the expression.
  • default: The value to return if none of the search values match the expression.

• CASE Syntax:

  • Simple CASE Expression:

    
    CASE expression
        WHEN value1 THEN result1
        WHEN value2 THEN result2
        ...
        ELSE default
    END
    

  • Searched CASE Expression:

    
    CASE
        WHEN condition1 THEN result1
        WHEN condition2 THEN result2
        ...
        ELSE default
    END
    

2. Functionality

• DECODE:

  • Acts like a simplified CASE expression.
  • Only compares a single expression against a series of possible values.
  • Stops evaluating once a match is found.
  • More compact and concise for simple equality checks.
  • Primarily available in Oracle databases.

• CASE:

  • More powerful and flexible than DECODE.
  • Can handle multiple conditions and logical expressions, not just equality checks.
  • Available in almost all major relational database management systems (RDBMS), including Oracle, SQL Server, MySQL, and PostgreSQL.
  • Provides both a simple case (for equality checks) and a searched case (for more complex conditions).

3. Portability

• DECODE:

  • Mostly specific to Oracle databases, so it is less portable across different RDBMS.
  • Not natively supported in SQL Server, MySQL, or PostgreSQL.

• CASE:

  • Standard SQL and widely supported across different RDBMS.
  • More portable, making it a better choice for SQL scripts that need to work across different database systems.

4. Use Cases

• DECODE:

  • Best for simple mappings and when working within Oracle.
  • Example:

    
    SELECT DECODE(status, 'A', 'Active', 'I', 'Inactive', 'Unknown') FROM users;
    

• CASE:

  • Preferred for complex conditions, non-Oracle databases, and where portability is a concern.
  • Example:

    
    SELECT 
        CASE 
            WHEN status = 'A' THEN 'Active'
            WHEN status = 'I' THEN 'Inactive'
            ELSE 'Unknown'
        END 
    FROM users;
    

5. Performance

• Performance is typically comparable between the two for simple use cases, but CASE can be more optimized and versatile for complex scenarios.

Conclusion:

• Use DECODE if you are working in Oracle and need a quick, simple mapping solution.
• Use CASE for more complex conditions, for better portability, and when working with non-Oracle databases.