#data engineering online course

[dataengineeringcourse]

Azure Data Engineering Training in Hyderabad

Master Data Engineering with Azure at RS Trainings

In today’s data-driven world, the role of a Data Engineer is more critical than ever. Data Engineers are the backbone of any data-centric enterprise, responsible for designing, building, and maintaining the infrastructure that allows data scientists and analysts to perform their work. If you're looking to excel in this field, RS Trainings offers the best Azure Data Engineering Training in Hyderabad, guided by industry IT experts.

Why Choose Data Engineering?

Data Engineering is pivotal for the efficient processing and storage of large datasets, which are crucial for deriving insights and making informed business decisions. As organizations continue to collect vast amounts of data, the demand for skilled Data Engineers who can manage and optimize this data is skyrocketing. Specializing in Azure Data Engineering means you’ll be equipped to work with Microsoft’s powerful cloud platform, widely adopted by enterprises for its scalability and robust features.

Azure Data Engineering Training at RS Trainings

RS Trainings is renowned for delivering comprehensive and practical training in Data Engineering. Our Azure Data Engineering course is meticulously designed to cover all essential aspects, from data integration and transformation to advanced data warehousing solutions.

Course Highlights:

Expert Instructors: Learn from seasoned industry IT professionals with extensive experience in Azure and Data Engineering.

Real-Time Practical Training: Our training emphasizes hands-on experience with real-time projects, ensuring you gain practical skills that can be directly applied in the workplace.

Comprehensive Curriculum: The course covers a wide range of topics, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and more.

Certification Preparation: Get ready for the Azure Data Engineer certification exam with our tailored preparation modules.

Flexible Learning Options: We offer both online and offline classes to suit your schedule and learning preferences.

Why RS Trainings?

At RS Trainings, we believe in delivering quality education that translates into real-world success. Our commitment to excellence, state-of-the-art training facilities, and personalized learning approach make us the preferred choice for aspiring Data Engineers in Hyderabad.

Enroll Today!

Join RS Trainings and embark on a journey to become a proficient Azure Data Engineer. Our expert-led training and practical approach will equip you with the skills needed to thrive in the ever-evolving field of Data Engineering. Contact us today to learn more about our Azure Data Engineering Training program and take the first step towards a successful career.

[iventmodel]

Who provides the best Informatica MDM training?

1. Introduction to Informatica MDM Training

Informatica MDM (Master Data Management) is a crucial aspect of data management for organizations dealing with large volumes of data. With the increasing demand for professionals skilled in Informatica MDM, the need for quality training has become paramount. Choosing the right training provider can significantly impact your learning experience and career prospects in this field.

2. Importance of Choosing the Right Training Provider

Selecting the best Informatica MDM training provider is essential for acquiring comprehensive knowledge, practical skills, and industry recognition. A reputable training provider ensures that you receive the necessary guidance and support to excel in your career.

3. Factors to Consider When Choosing Informatica MDM Training

Reputation and Experience

A reputable training provider should have a proven track record of delivering high-quality training and producing successful professionals in the field of Informatica MDM.

Course Curriculum

The course curriculum should cover all essential aspects of Informatica MDM, including data modeling, data integration, data governance, and data quality management.

Training Methodology

The training methodology should be interactive, engaging, and hands-on, allowing participants to gain practical experience through real-world scenarios and case studies.

Instructor Expertise

Experienced and certified instructors with extensive knowledge of Informatica MDM ensure effective learning and provide valuable insights into industry best practices.

Flexibility of Learning Options

Choose a training provider that offers flexible learning options such as online courses, instructor-led classes, self-paced learning modules, and blended learning approaches to accommodate your schedule and learning preferences.

4. Comparison of Training Providers

When comparing Informatica MDM training providers, consider factors such as cost, course duration, support services, and reviews from past participants. Choose a provider that offers the best value for your investment and aligns with your learning objectives and career goals.

5. Conclusion

Selecting the right Informatica MDM training provider is crucial for acquiring the necessary skills and knowledge to succeed in this competitive field. Evaluate different providers based on factors such as reputation, course curriculum, instructor expertise, and flexibility of learning options to make an informed decision.

Contact us 👇

📞Call Now: +91-9821931210 📧E Mail: support@inventmodel.com 🌐Visit Website: https://inventmodel.com/course/informatica-mdm-online-live-training

[bizschoolkol]

Cloud Data Engineering Courses: Your Path to an Industry-Ready Career

Discover how cloud data engineering courses equip you with essential skills for the modern tech industry. Learn data integration, management, and cloud computing to boost your career prospects and stay ahead in the competitive job market.

[a-guide-to-mastering-the-future]

We’re excited to announce our upcoming courses at IIBS College! With confirmed batches launching on January 11, 2025, now is the perfect time to enroll and expand your skill set in high-demand fields.

*Hurry up to avail the New Year’s Discount!

[datasciencewithgenerativeai]

Azure Data Engineer Training Online in Hyderabad | Azure Data Engineer Training

How to Connect to Key Vaults from Azure Data Factory?

Introduction Azure Data Engineer Online Training Azure Key Vault is a secure cloud service that provides the ability to safeguard cryptographic keys and secrets. These secrets could be tokens, passwords, certificates, or API keys. Integrating Key Vault with Azure Data Factory (ADF) allows you to securely manage and access sensitive data without exposing it directly in your pipelines. This article explains how to connect to Key Vaults from Azure Data Factory and securely manage your credentials. Azure Data Engineer Training

Setting Up Azure Key Vault and Azure Data Factory Integration

Create a Key Vault and Store Secrets

Create Key Vault: Navigate to the Azure portal and create a new Key Vault instance.

Store Secrets: Store the secrets (e.g., database connection strings, API keys) in the Key Vault by defining name-value pairs.

Set Access Policies

Assign Permissions: In the Key Vault, go to “Access policies” and select the permissions (Get, List) necessary for Data Factory to retrieve secrets.

Select Principal: Add Azure Data Factory as the principal in the access policy, allowing the pipeline to access the secrets securely.

Connecting Azure Data Factory to Key Vault

Use Linked Services

Create Linked Service for Key Vault: Go to the Manage section in Azure Data Factory, then select “Linked Services” and create a new one for Key Vault.

Configure Linked Service: Input the details such as subscription, Key Vault name, and grant access through a Managed Identity or Service Principal.

Access Secrets in Pipelines Once your Key Vault is linked to Azure Data Factory, you can retrieve secrets within your pipelines without hardcoding sensitive information. This can be done by referencing the secrets dynamically in pipeline activities.

Dynamic Secret Reference: Use expressions to access secrets from the linked Key Vault, such as referencing connection strings or API keys during pipeline execution.

Benefits of Using Key Vault with Azure Data Factory

Enhanced Security By centralizing secret management in Key Vault, you reduce the risk of data leaks and ensure secure handling of credentials in Azure Data Factory pipelines.

Simplified Management Key Vault simplifies credential management by eliminating the need to embed secrets directly in the pipeline. When secrets are updated in the Key Vault, no changes are required in the pipeline code.

Auditing and Compliance Key Vault provides built-in logging and monitoring for tracking access to secrets, helping you maintain compliance and better governance.

Conclusion Connecting Azure Key Vault to Azure Data Factory enhances the security and management of sensitive data in pipelines. With simple integration steps, you can ensure that secrets are stored and accessed securely, improving overall compliance and governance across your data solutions.

Visualpath is the Leading and Best Software Online Training Institute in Hyderabad. Avail complete Azure Data Engineer Training Online in Hyderabad Worldwide You will get the best course at an affordable cost.

Attend Free Demo

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[mitsde123]

How to Choose the Right Machine Learning Course for Your Career

As the demand for machine learning professionals continues to surge, choosing the right machine learning course has become crucial for anyone looking to build a successful career in this field. With countless options available, from free online courses to intensive boot camps and advanced degrees, making the right choice can be overwhelming. 

[googleclouddataengineertraining]

Learn With India's Biggest Enterprise Training Provider. we provides participants a hands-on introduction to designing and building on  Google Cloud. Only institution in India that is Onlineitguru You can schedule a free demo on Google Cloud Data Engineer Online Training by contacting us   +91 9550102466 https://onlineitguru.com/google-cloud-data-engineer-training

[techcoursetrend]

Power BI Training in Hyderabad

Power BI Training in Hyderabad: Unlocking Data Insights with RS Trainings

In today’s data-driven world, the ability to interpret and make informed decisions from data is a valuable skill across industries. Microsoft Power BI, a powerful business analytics tool, has become the go-to choice for organizations looking to gain data insights, visualize trends, and share meaningful reports. For professionals and aspiring analysts, mastering Power BI opens up a world of possibilities in data analytics and business intelligence. RS Trainings in Hyderabad stands out as one of the best institutions to help you gain proficiency in Power BI, offering top-notch training led by seasoned Industry IT experts.

Why Choose Power BI?

Power BI has rapidly gained popularity due to its user-friendly interface, robust data integration capabilities, and interactive visualizations. It enables users to:

Analyze Data from Multiple Sources: With Power BI, you can import data from various sources such as Excel, SQL databases, cloud services, and web data, making it a versatile tool for handling multiple data streams.

Create Interactive Dashboards: Power BI’s visualizations allow users to create engaging, interactive dashboards that help track key metrics and performance indicators.

Share Insights Across Teams: Power BI’s cloud-based services make it easy to share insights with colleagues and stakeholders in real time, allowing collaborative data-driven decision-making.

Make Data-Driven Decisions: Through its advanced AI capabilities, Power BI provides predictive insights, enabling businesses to anticipate trends and act proactively.

RS Trainings: The Best Place for Power BI Training in Hyderabad

RS Trainings is renowned for its comprehensive Power BI training program, designed to equip learners with the skills and expertise they need to succeed in data analytics. Here’s what sets RS Trainings apart as the best place to learn Power BI in Hyderabad:

1. Industry-Experienced Trainers

At RS Trainings, you’ll learn from top IT industry experts who bring real-world experience to the classroom. These instructors have a deep understanding of Power BI and its applications across industries. Their hands-on insights and practical examples give students a strong foundation in data analytics and reporting.

2. Comprehensive Curriculum

RS Trainings offers a well-structured Power BI curriculum that covers everything from the basics to advanced features. Students learn about data transformation, data modeling, DAX (Data Analysis Expressions), and advanced visualizations. The curriculum is designed to ensure learners gain all the necessary skills to create impactful reports and dashboards.

3. Practical Learning with Real-Time Projects

One of the unique aspects of RS Trainings’ Power BI course is its focus on practical, hands-on experience. The program includes real-time projects where students work on real-world scenarios, applying their knowledge to analyze data and present insights. This practical approach helps students gain the confidence they need to tackle business challenges.

4. Flexible Learning Options

RS Trainings understands the need for flexibility, especially for working professionals. They offer a range of learning options, including online classes, weekend batches, and classroom training sessions. This allows students to choose the format that best fits their schedule and learning style.

5. Placement Assistance and Career Support

Completing Power BI training at RS Trainings also gives students access to placement assistance and career support. With connections to top MNCs, RS Trainings helps students navigate job opportunities, prepare for interviews, and take the next steps in their data analytics careers.

What Will You Learn in RS Trainings’ Power BI Course?

The Power BI training at RS Trainings covers key topics essential to mastering the tool:

Data Import and Transformation: Learn how to connect Power BI to various data sources, clean and transform data, and prepare it for analysis.

Data Modeling: Discover how to design data models and create relationships between datasets for meaningful insights.

DAX Functions: Gain proficiency in DAX to perform calculations, create custom columns, and enhance data analysis.

Interactive Visualizations: Learn to create dynamic, interactive dashboards and reports using various visualization options in Power BI.

Report Publishing and Sharing: Understand how to publish reports and share insights through Power BI services, enabling effective collaboration and decision-making.

Why RS Trainings is the Right Choice for Power BI Training

In Hyderabad, RS Trainings has established itself as a top provider of Power BI training due to its commitment to delivering high-quality education led by industry experts. For those looking to boost their career in data analytics or become proficient in Power BI, RS Trainings provides a supportive, industry-aligned training environment that ensures students get the best learning experience.

Final Thoughts

Mastering Power BI can significantly boost your career prospects in today’s data-focused job market. RS Trainings in Hyderabad offers one of the best training programs for Power BI, combining expert instruction, hands-on projects, and flexible learning options. Whether you’re a beginner in data analytics or an experienced professional looking to upgrade your skills, RS Trainings has the resources and expertise to guide you on your journey to Power BI mastery.

[1stepgrow]

Explore Data Analyst, Machine Learning Engineer, and Data Scientist roles. Acquire skills like programming, statistics, and ML algorithms. Gain experience through education, projects, and internships for career advancement. For more information Please visit the 1stepGrow website or best data science course.

[scholarnest]

From Beginner to Pro: The Best PySpark Courses Online from ScholarNest Technologies

Are you ready to embark on a journey from a PySpark novice to a seasoned pro? Look no further! ScholarNest Technologies brings you a comprehensive array of PySpark courses designed to cater to every skill level. Let's delve into the key aspects that make these courses stand out:

1. What is PySpark?

Gain a fundamental understanding of PySpark, the powerful Python library for Apache Spark. Uncover the architecture and explore its diverse applications in the world of big data.

2. Learning PySpark by Example:

Experience is the best teacher! Our courses focus on hands-on examples, allowing you to apply your theoretical knowledge to real-world scenarios. Learn by doing and enhance your problem-solving skills.

3. PySpark Certification:

Elevate your career with our PySpark certification programs. Validate your expertise and showcase your proficiency in handling big data tasks using PySpark.

4. Structured Learning Paths:

Whether you're a beginner or seeking advanced concepts, our courses offer structured learning paths. Progress at your own pace, mastering each skill before moving on to the next level.

5. Specialization in Big Data Engineering:

Our certification course on big data engineering with PySpark provides in-depth insights into the intricacies of handling vast datasets. Acquire the skills needed for a successful career in big data.

6. Integration with Databricks:

Explore the integration of PySpark with Databricks, a cloud-based big data platform. Understand how these technologies synergize to provide scalable and efficient solutions.

7. Expert Instruction:

Learn from the best! Our courses are crafted by top-rated data science instructors, ensuring that you receive expert guidance throughout your learning journey.

8. Online Convenience:

Enroll in our online PySpark courses and access a wealth of knowledge from the comfort of your home. Flexible schedules and convenient online platforms make learning a breeze.

Whether you're a data science enthusiast, a budding analyst, or an experienced professional looking to upskill, ScholarNest's PySpark courses offer a pathway to success. Master the skills, earn certifications, and unlock new opportunities in the world of big data engineering! 

[datavalleyai]

50 Big Data Concepts Every Data Engineer Should Know

Big data is the primary force behind data-driven decision-making. It enables organizations to acquire insights and make informed decisions by utilizing vast amounts of data. Data engineers play a vital role in managing and processing big data, ensuring its accessibility, reliability, and readiness for analysis. To succeed in this field, data engineers must have a deep understanding of various big data concepts and technologies.

This article will introduce you to 50 big data concepts that every data engineer should know. These concepts encompass a broad spectrum of subjects, such as data processing, data storage, data modeling, data warehousing, and data visualization.

1. Big Data

Big data refers to datasets that are so large and complex that traditional data processing tools and methods are inadequate to handle them effectively.

2. Volume, Velocity, Variety

These are the three V’s of big data. Volume refers to the sheer size of data, velocity is the speed at which data is generated and processed, and variety encompasses the different types and formats of data.

3. Structured Data

Data that is organized into a specific format, such as rows and columns, making it easy to query and analyze. Examples include relational databases.

4. Unstructured Data

Data that lacks a predefined structure, such as text, images, and videos. Processing unstructured data is a common challenge in big data engineering.

5. Semi-Structured Data

Data that has a partial structure, often in the form of tags or labels. JSON and XML files are examples of semi-structured data.

6. Data Ingestion

The process of collecting and importing data into a data storage system or database. It’s the first step in big data processing.

7. ETL (Extract, Transform, Load)

ETL is a data integration process that involves extracting data from various sources, transforming it to fit a common schema, and loading it into a target database or data warehouse.

8. Data Lake

A centralized repository that can store vast amounts of raw and unstructured data, allowing for flexible data processing and analysis.

9. Data Warehouse

A structured storage system designed for querying and reporting. It’s used to store and manage structured data for analysis.

10. Hadoop

An open-source framework for distributed storage and processing of big data. Hadoop includes the Hadoop Distributed File System (HDFS) and MapReduce for data processing.

11. MapReduce

A programming model and processing technique used in Hadoop for parallel computation of large datasets.

12. Apache Spark

An open-source, cluster-computing framework that provides in-memory data processing capabilities, making it faster than MapReduce.

13. NoSQL Databases

Non-relational databases designed for handling unstructured and semi-structured data. Types include document, key-value, column-family, and graph databases.

14. SQL-on-Hadoop

Technologies like Hive and Impala that enable querying and analyzing data stored in Hadoop using SQL-like syntax.

15. Data Partitioning

Dividing data into smaller, manageable subsets based on specific criteria, such as date or location. It improves query performance.

16. Data Sharding

Distributing data across multiple databases or servers to improve data retrieval and processing speed.

17. Data Replication

Creating redundant copies of data for fault tolerance and high availability. It helps prevent data loss in case of hardware failures.

18. Distributed Computing

Computing tasks that are split across multiple nodes or machines in a cluster to process data in parallel.

19. Data Serialization

Converting data structures or objects into a format suitable for storage or transmission, such as JSON or Avro.

20. Data Compression

Reducing the size of data to save storage space and improve data transfer speeds. Compression algorithms like GZIP and Snappy are commonly used.

21. Batch Processing

Processing data in predefined batches or chunks. It’s suitable for tasks that don’t require real-time processing.

22. Real-time Processing

Processing data as it’s generated, allowing for immediate insights and actions. Technologies like Apache Kafka and Apache Flink support real-time processing.

23. Machine Learning

Using algorithms and statistical models to enable systems to learn from data and make predictions or decisions without explicit programming.

24. Data Pipeline

A series of processes and tools used to move data from source to destination, often involving data extraction, transformation, and loading (ETL).

25. Data Quality

Ensuring data accuracy, consistency, and reliability. Data quality issues can lead to incorrect insights and decisions.

26. Data Governance

The framework of policies, processes, and controls that define how data is managed and used within an organization.

27. Data Privacy

Protecting sensitive information and ensuring that data is handled in compliance with privacy regulations like GDPR and HIPAA.

28. Data Security

Safeguarding data from unauthorized access, breaches, and cyber threats through encryption, access controls, and monitoring.

29. Data Lineage

A record of the data’s origins, transformations, and movement throughout its lifecycle. It helps trace data back to its source.

30. Data Catalog

A centralized repository that provides metadata and descriptions of available datasets, making data discovery easier.

31. Data Masking

The process of replacing sensitive information with fictional or scrambled data to protect privacy while preserving data format.

32. Data Cleansing

Identifying and correcting errors or inconsistencies in data to improve data quality.

33. Data Archiving

Moving data to secondary storage or long-term storage to free up space in primary storage and reduce costs.

34. Data Lakehouse

An architectural approach that combines the benefits of data lakes and data warehouses, allowing for both storage and structured querying of data.

35. Data Warehouse as a Service (DWaaS)

A cloud-based service that provides on-demand data warehousing capabilities, reducing the need for on-premises infrastructure.

36. Data Mesh

An approach to data architecture that decentralizes data ownership and management, enabling better scalability and data access.

37. Data Governance Frameworks

Defined methodologies and best practices for implementing data governance, such as DAMA DMBOK and DCAM.

38. Data Stewardship

Assigning data stewards responsible for data quality, security, and compliance within an organization.

39. Data Engineering Tools

Software and platforms used for data engineering tasks, including Apache NiFi, Talend, Apache Beam, and Apache Airflow.

40. Data Modeling

Creating a logical representation of data structures and relationships within a database or data warehouse.

41. ETL vs. ELT

ETL (Extract, Transform, Load) involves extracting data, transforming it, and then loading it into a target system. ELT (Extract, Load, Transform) loads data into a target system before performing transformations.

42. Data Virtualization

Providing a unified view of data from multiple sources without physically moving or duplicating the data.

43. Data Integration

Combining data from various sources into a single, unified view, often involving data consolidation and transformation.

44. Streaming Data

Data that is continuously generated and processed in real-time, such as sensor data and social media feeds.

45. Data Warehouse Optimization

Improving the performance and efficiency of data warehouses through techniques like indexing, partitioning, and materialized views.

46. Data Governance Tools

Software solutions designed to facilitate data governance activities, including data cataloging, data lineage, and data quality tools.

47. Data Lake Governance

Applying data governance principles to data lakes to ensure data quality, security, and compliance.

48. Data Curation

The process of organizing, annotating, and managing data to make it more accessible and valuable to users.

49. Data Ethics

Addressing ethical considerations related to data, such as bias, fairness, and responsible data use.

50. Data Engineering Certifications

Professional certifications, such as the Google Cloud Professional Data Engineer or Microsoft Certified: Azure Data Engineer, that validate expertise in data engineering.

Elevate Your Data Engineering Skills

Data engineering is a dynamic field that demands proficiency in a wide range of concepts and technologies. To excel in managing and processing big data, data engineers must continually update their knowledge and skills.

If you’re looking to enhance your data engineering skills or start a career in this field, consider enrolling in Datavalley’s Big Data Engineer Masters Program. This comprehensive program provides you with the knowledge, hands-on experience, and guidance needed to excel in data engineering. With expert instructors, real-world projects, and a supportive learning community, Datavalley’s course is the ideal platform to advance your career in data engineering.

Don’t miss the opportunity to upgrade your data engineering skills and become proficient in the essential big data concepts. Join Datavalley’s Data Engineering Course today and take the first step toward becoming a data engineering expert. Your journey in the world of data engineering begins here.

[techwondersunveiled]

AZ 900 - Azure fundamentals exam questions| Latest series |Part 11

[pythoncourse123]

Data Engineer Training in Hyderabad

Empowering Your Data Journey: RS Training's Premier Data Engineering Training in Hyderabad

In today's data-driven landscape, the role of data engineers has become indispensable. These professionals play a crucial role in designing, constructing, and maintaining the infrastructure necessary for efficient data processing and analysis. To embark on a successful career in data engineering or elevate your existing skills, look no further than RS Training, the leading provider of Data Engineer training in Hyderabad, guided by real-time industry experts.

Why Data Engineering Matters?

Data engineering is the backbone of any data-driven organization. It involves the process of collecting, storing, and preparing data for analysis. Data engineers build and manage data pipelines, ensuring that data is accessible, reliable, and ready for use by data analysts and data scientists. In essence, data engineering is the foundation upon which data-driven decisions are made.

Why RS Training's Data Engineer Training?

RS Training's Data Engineer training program is the gateway to mastering the critical skills required in the field of data engineering. Here's why RS Training stands out as the best choice for Data Engineer training in Hyderabad:

1. Industry Experts as Instructors:

RS Training prides itself on its team of real-time industry experts who bring their wealth of knowledge and experience to the classroom. They provide practical insights and hands-on guidance, ensuring that you are well-prepared for the challenges of the real-world data engineering landscape.

2. Comprehensive Curriculum:

The Data Engineer training program at RS Training is thoughtfully structured to cover the full spectrum of data engineering concepts and tools. From data ingestion and storage to data transformation and processing, you will gain in-depth knowledge and skills.

3. Hands-On Learning:

RS Training believes in learning by doing. Their training approach is highly practical, with extensive hands-on exercises and real-world projects. This ensures that you not only understand the theory but also gain the confidence to apply your skills in real-world scenarios.

4. Flexibility and Customization:

RS Training offers flexible training options, including online and offline classes, weekend batches, and customized corporate training. This flexibility caters to diverse learning needs and schedules.

5. Certification Assistance:

RS Training supports you in preparing for relevant certifications in data engineering. Earning certifications can enhance your credibility and career prospects in the field.

6. Continuous Support:

Your journey with RS Training doesn't end with the course. They provide ongoing support and resources to help you stay updated with the latest developments in data engineering.

7. State-of-the-Art Facilities:

RS Training provides a state-of-the-art learning environment with access to the latest data engineering tools and technologies.

Join RS Training and Unleash Your Data Engineering Potential!

RS Training's commitment to excellence and its alignment with industry requirements make it the top choice for Data Engineer training in Hyderabad. Whether you're a novice looking to start a rewarding career in data engineering or a professional aiming to upskill and advance your career, RS Training has the expertise and resources to help you succeed. Join RS Training and embark on a transformative journey into the world of data engineering with the guidance of real-time industry experts. Your path to becoming a proficient data engineer begins here.

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Attend Online #New Batch on #AWSDataEngineering with #DataAnalytics by Mr. Sathish.

Demo on: 2nd April, 2024@ 8:00 PM (IST).

Contact us: +91 9989971070.

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