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What do you do if cloud computing is changing the landscape of data warehousing careers?

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Cloud computing is transforming the way data is stored, processed, and analyzed. As a data warehousing professional, you may wonder how this affects your career and what skills you need to stay relevant. In this article, we will explore some of the challenges and opportunities that cloud computing brings to data warehousing, and how you can adapt and thrive in this changing landscape.

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1 Cloud vs. on-premise data warehousing

Traditionally, data warehousing involved building and maintaining a centralized repository of data from various sources, using on-premise hardware and software. This required significant upfront investment, ongoing maintenance, and scalability challenges. Cloud computing, on the other hand, offers a more flexible, cost-effective, and scalable alternative, where data can be stored and accessed on demand, using remote servers and services provided by cloud vendors. Cloud data warehousing also enables faster and easier integration of data from different sources, such as web, mobile, social media, and IoT.

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Diwakar Reddy

Data Engineer | SQL | SSIS | Tera Data | Control M | DBT, Airflow
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Skill Upgradation: Stay updated with the latest cloud computing technologies and platforms, such as AWS, Azure, GCP Learn DW in the Cloud: Familiarize yourself with cloud-based data warehousing solutions like Amazon Redshift, Google BigQuery, Snowflake, and Azure Synapse Analytics. DE Skills: Enhance your data engineering skills to efficiently manage and process data in cloud environments. Adaptability: Embrace change and be open to learning new technologies and methodologies. Focus on Automation and Scalability: Understand how to leverage cloud-based tools for automating data processing tasks and scaling Networking with people Continuous Learning: Make a commitment to lifelong learning by regularly seeking out new educational resources

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Muhammad Nadeem

Head of Data Engineering / Analytics
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Cloud Computing's Effect on Data Warehousing Careers ? Become familiar with key cloud systems such as AWS, Microsoft Azure, and Google Cloud Platform. ? Learn about their data warehousing services, including AWS Redshift, Azure SQL Data Warehouse, and Google BigQuery. ? Learn about cloud technologies related to data warehousing, such as cloud storage solutions, data lakes, serverless computing, and containers. ? Gain expertise in data engineering, including data pipeline construction, data integration, ETL procedures, and data governance. ? Investigate machine learning and analytics solutions that interface with cloud data warehouses for advanced analytics, predictive modeling, and data visualization.

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Sashanth Embakula

Data Analyst @CapitalOne | Microsoft Certified Azure Data Engineer | AWS Certified Solutions Architect | Snowflake | PySpark | AWS | Azure | Airflow | Python | SQL
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Understand the fundamental differences between traditional on-premise data warehousing and modern cloud-based solutions. Cloud data warehousing platforms, such as AWS Redshift, Google BigQuery, Azure Synapse Analytics, and Snowflake, offer scalability, flexibility, and cost-effectiveness that on-premise solutions struggle to match. Familiarize yourself with the concepts of cloud storage, compute resources, and services to appreciate how cloud solutions can streamline data integration from diverse sources.

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2 Benefits and drawbacks of cloud data warehousing

Cloud data warehousing has many advantages over on-premise data warehousing, such as reduced costs, improved performance and availability, enhanced security and compliance, and greater scalability and elasticity. However, there are also some drawbacks to consider. Dependency on the cloud vendor's platform and services can lead to lock-in, while data governance and quality issues may arise from losing control over data sources. Additionally, network and latency challenges can cause delays or disruptions in accessing or transferring data.

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Sashanth Embakula

Data Analyst @CapitalOne | Microsoft Certified Azure Data Engineer | AWS Certified Solutions Architect | Snowflake | PySpark | AWS | Azure | Airflow | Python | SQL
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Gain knowledge of the advantages of cloud data warehousing, including cost savings on hardware and maintenance, improved scalability, and enhanced data security features offered by cloud providers. However, also be aware of potential challenges, such as vendor lock-in, data governance complexities, and the need for robust internet connectivity. Understanding these pros and cons will enable you to make informed decisions and provide valuable insights to your organization.

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3 Skills and competencies for cloud data warehousing

To succeed in cloud data warehousing, you need to update your skills and competencies to meet the new demands and opportunities. This includes understanding cloud computing fundamentals, such as architecture, models, services, and security aspects. Additionally, you should be familiar with cloud data warehousing tools and platforms like AWS Redshift, Google BigQuery, Microsoft Azure Synapse, or Snowflake. Moreover, data integration and ETL (extract, transform, load) techniques should be mastered in order to ingest, transform, and load data from various sources. Furthermore, data analysis and visualization skills are essential for querying, analyzing, and visualizing data from the cloud data warehouse. Lastly, having knowledge of data engineering and architecture will help you design and optimize cloud data warehouse solutions that meet business needs and objectives.

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4 Learning resources for cloud data warehousing

If you want to learn more about cloud data warehousing and improve your skills and competencies, there are many resources available online. For instance, Coursera's Data Warehousing for Business Intelligence Specialization, Udemy's Cloud Data Warehousing with Google BigQuery, or AWS's Data Warehousing on AWS provide online courses and certifications. Additionally, Cloud Data Warehouse, Cloud Data Engineering, or Data Engineering Podcast are blogs and podcasts that can be accessed. Lastly, books and ebooks such as Cloud Data Warehousing: A Practical Guide, Data Warehouse in the Cloud, or Data Warehouse Automation in Azure for Dummies are also available.

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5 Tips and best practices for cloud data warehousing

If you want to succeed in cloud data warehousing, you should choose the right platform and service that suits your needs. Compare the features, benefits, and drawbacks of different options, and consider factors such as performance, scalability, security, and compatibility. When planning and designing your cloud data warehouse solution, make sure to follow the best practices and standards for data warehousing. Additionally, you should monitor and optimize your cloud data warehouse performance and costs by tracking and analyzing your data storage, data processing, and data consumption. You can also use techniques such as compression, caching, and archiving to reduce your data footprint and costs. Finally, it’s important to stay on top of the latest trends in cloud data warehousing by learning new skills and seeking feedback from experts.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Fawad A. Qureshi

Field CTO @ Snowflake | LinkedIn Learning Instructor | Sustainability ??, Data Strategy, Business Transformation
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Data is data, whether it is in the cloud or on-premises; the core analytical concepts remain the same. What changes are there in infrastructure provisioning and the different as-a-service delivery models. If you are already a data expert who has primarily worked in on-premises deployments, then take a course on infrastructure provisioning to learn what are the as-a-service models. How do we avoid bill shocks, etc? You should be good to go in the cloud world.

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What do you do if cloud computing is changing the landscape of data warehousing careers?

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6

1 Cloud vs. on-premise data warehousing

2 Benefits and drawbacks of cloud data warehousing

3 Skills and competencies for cloud data warehousing

4 Learning resources for cloud data warehousing

5 Tips and best practices for cloud data warehousing

6 Here’s what else to consider

Data Warehousing

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What do you do if cloud computing is changing the landscape of data warehousing careers?

1

2

3

4

5

6

1 Cloud vs. on-premise data warehousing

2 Benefits and drawbacks of cloud data warehousing

3 Skills and competencies for cloud data warehousing

4 Learning resources for cloud data warehousing

5 Tips and best practices for cloud data warehousing

6 Here’s what else to consider

Data Warehousing

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