High-quality data that’s centrally stored, universally available, and easy to analyze is one of the big things that makes a business if you have it or breaks it if you don’t. Data management is the umbrella term for all the processes, technologies, and practices that make this possible. To remain competitive and innovate, modern enterprises have to use some mix of cloud data management – from fully managed data to hybrid cloud.
On-premise hardware is expensive, complex to maintain, and not as scalable as cloud data services. Sometimes it makes sense to use on-premise data infrastructure, but as cloud technology and security advances those use cases are disappearing every year. More and more enterprises trust cloud data management providers like AWS, Azure, Snowflake, and Google cloud to make their data accessible, secure, and valuable.
Here’s everything you need to know about cloud data management and how to hire a senior DataOps team in 4-6 weeks to help you reach your data goals.
What is cloud data management?
Cloud data management is the practice of managing, storing, organizing, and analyzing data within cloud-based applications and infrastructure. It includes processes, technologies, workflows that align with the broader goals of data management but it all happens in a cloud computing environment.
These include data storage, integration, transformation, backup, recovery, security, compliance, and analytics – all tailored to the virtualized and distributed nature of cloud platforms. When your data is managed in the cloud it also makes it easier to move into cloud-native architecture and development, microservices, API-first design, containerization, AI/ML capabilities, and DevOps practices like CI/CD.
Cloud data management supports modern software development
Modern application development (MAD) enables you to design, develop, deploy, and manage modern applications faster. These technologies, platforms, methodologies, and professional services create scalable, responsive, flexible software solutions that meet the evolving needs of your users and business in the digital era.
For example, if you can find a MAD services provider to implement Azure platform-as-a-service (PaaS), you get some huge benefits:
- 50% increase in the speed of software development
- 228 percent return on investment (ROI) in three years
- 40 percent reduction in app and dev-related infrastructure costs
You might have some of these huge modern software development goals on your roadmap. And each one is made easier to achieve when you manage your data in the cloud.
- Cloud-native architecture and development
- Microservices and containerization
- API-first design and developer gateways
- AI/ML design and implementation
- DevOps and CI/CD tools
- Enterprise systems integration
Aside from cloud data management being a crucial foundation for many other technology initiatives, it comes with some significant benefits all on its own.
Business benefits of cloud data management
- Cost efficiency: Pay-as-you-go model enables access to data management without heavy investments.
- Global collaboration: Cloud platforms foster seamless collaboration from anywhere, at any time, supporting remote work and distributed organizations.
- Enhanced security: Leverages cloud providers' investments in security technologies and certifications.
- Regulatory compliance: Helps in adherence to various regulatory requirements and standards, reducing legal risks.
- Sustainable and environmentally friendly: Shared cloud infrastructure supports energy-efficient computing.
- Strategic focus: Offloads data management complexity, allowing focus on core business strategies.
Business capabilities you get from cloud data management
Handling your data management to the cloud opens up everything from improved customer experience personalization to software development automation. You’ll open up collaboration across the whole business while making it easier to design, build, and deploy new applications and customer experiences.
Here are the main business capabilities that have CIOs, CTOs, and VPs of Engineering investing in cloud data management instead of on-premise infrastructure.
- Scalability and flexibility: Cloud data management allows your business to scale data needs up or down based on demand. This adaptability lets you respond to fluctuating market conditions and customer requirements without heavy upfront investment in infrastructure.
- Real-time analytics and insights: Leveraging cloud-based analytics tools, you can get real-time insights into operations, customers, markets, and revenue performance. These insights pave the way for informed decision-making across your whole organization.
- Disaster recovery and business continuity: Cloud data management offers robust disaster recovery solutions – enabling rapid restoration of data and operations following a system failure or catastrophic event. This ensures business continuity and minimizes downtime – which is crucial as more and more climate events impact the world.
- Global reach and localization: Cloud data services give you the flexibility to expand into global markets more easily by offering data localization and compliance with local regulations. This supports international growth and reaching into new markets.
- Innovation and new technology: Access to the latest data technologies and platforms allows businesses to develop and deploy new products and services more swiftly. This access nurtures innovation and enables organizations to respond promptly to emerging opportunities and threats.
- Personalized customer experiences: Cloud data analytics and AI tools enable businesses to understand customer behavior and preferences in-depth. They can leverage this information to create personalized experiences, thereby enhancing customer satisfaction and loyalty.
- Automated workflows and processes: Cloud data management underpins the automation and orchestration of data workflows. By reducing manual efforts and minimizing errors, automation liberates staff to focus on more strategic tasks.
- Seamless integration with partners and vendors: Cloud-based data exchange facilitates easier integration with suppliers, partners, and vendors, creating a more responsive and flexible supply chain.
Components of cloud data management
Cloud data management is an umbrella for a long list of data operations. It includes everything from data storage and data transformation to data analytics and visualization.
- Data storage: Utilizes cloud repositories for scalable, cost-effective storage that adapt to business needs.
- Data integration: Integrates data from diverse sources to build a unified view and seamless flow using tools like ETL.
- Data transformation: Modifies and converts data for compatibility across applications or databases, often using ETL tools.
- Data backup and recovery: Provides regular backups and recovery plans – ensuring global availability of critical data.
- Data quality management: Validates, cleans, and transforms data – unlocking reliable analytics and decision-making.
- Data security: Implements encryption, access control, and identity management to protect sensitive data.
- Data governance: Develops guidelines and policies for data ownership, usage, and quality.
- Data analytics and intelligence: Uses tools and algorithms to transform data into actionable insights for informed decisions.
- Data orchestration and automation: Coordinates and automates data tasks for efficient operations.
- Disaster recovery planning: Crafts strategies for data and system recovery after catastrophic failures.
- Data migration: Facilitates secure transfer of data between various platforms, ensuring no loss or downtime.
Each one of these components of cloud data management is handled by a complex data stack. You might use AWS for production databases and Snowflake for your cloud data warehouse.
While it’ll take more in-depth effort, research, and time to build your data stack, here are some of the best data tools and technologies that modern enterprises trust.
Technology and tools for cloud data management
Technology serves as the foundation of cloud data management. It is not merely about adopting the latest, fanciest tools but selecting the right platforms and technologies that align with business goals.
A well-orchestrated technology stack ensures seamless operations, secure storage, and the efficient utilization of data.
- Cloud storage solutions: Platforms like Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage, or Snowflake provide robust storage solutions that adapt to various data types. These platforms offer different storage classes, balancing cost and accessibility, and include features like versioning and lifecycle management to optimize storage.
- Data integration platforms: Tools like Apache NiFi, Talend, and Informatica enable seamless data integration. They streamline data movement between various sources and destinations, providing capabilities like data ingestion, transformation, and real-time processing.
- Data transformation tools: ETL (Extract, Transform, Load) tools like Apache Spark, AWS Glue, or Microsoft SSIS offer flexible data transformation capabilities. They allow your DataOps team to manipulate data in transit – transforming it into the desired format and structure that meets specific analytical needs.
- Database services: Services like Azure SQL Database, Amazon RDS, or MongoDB Atlas offer managed database solutions. These platforms relieve the burdens and costs of manual database management. They provide automated backups, scaling, and performance tuning, catering to various relational and non-relational data models.
- Data security technologies: Security technologies such as encryption, Identity and Access Management (IAM), and VPNs ensure secure data within the cloud. Implementing multi-factor authentication, data masking, and encryption at rest and in transit helps protect sensitive information and maintain compliance with regulations.
- Data analytics tools: Platforms like AWS Redshift, Google BigQuery, or Apache Hadoop allow complex data analysis. These tools support various data processing and analytical frameworks, enabling organizations to derive insights, forecast trends, and make data-driven decisions.
- Backup and recovery software: Cloud-optimized solutions like Veeam, Acronis, or Zerto protect against accidental loss or failure. They provide automated backup schedules, instant recovery options, and replication capabilities that safeguard essential data assets, ensuring business continuity.
- Data and container orchestration tools: Solutions like Kubernetes, Docker, or Terraform facilitate the orchestration and automation of data workflows. They simplify the deployment, scaling, and management of containerized applications, providing a unified environment that enhances collaboration and agility.
By understanding and investing in these technologies, you can unlock the full potential of your data. Unless, you don’t know how they all fit together, which most people don’t. That’s why hiring an expert team of cloud data architects, engineers, and agile product pros is crucial.
They’ll be able to tell you whether or not you actually need to replatform or just need a standalone ETL tool.
While they’re in high demand, expensive, and hard to find, you can hire these DataOps pros internally (which takes a long time) or find a MAD services provider who can build you a team in 4-6 weeks.
How do I hire a cloud data management team I can trust in 4-6 weeks?
You could make serious progress on your cloud data initiatives by next quarter instead of waiting 6-18 months to hire the right internal team. That’s why Codingscape exists. We can assemble a senior cloud data management team for you in 4-6 weeks. It’ll be faster to get started, more cost efficient than internal hiring, and we’ll deliver high-quality results quickly.
We’re not a software engineer recruiting agency either. You scope out the work with us, and we’ll integrate with your team, technology stack, and partner with you for as long as you need us.
Zappos, Twilio, and Veho are just a few companies that trust us to build software with a remote-first approach. We know cloud data management at scale and love to help companies take full advantage of cloud-native capabilities like containerization and microservices.
You can schedule a time to talk with us here. No hassle, no expectations, just answers.
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Cole is Codingscape's Content Marketing Strategist & Copywriter.