In recent years, the era of data storage has changed drastically. Enterprises swiftly shifted from legacy architecture to secure cloud storage. Yet, despite the continuous advancements in cloud transformations, businesses need a one-stop solution for their data-related concerns. That’s where Data Cloud Experience comes into play – a platform that enables you to manage multiple workloads under one roof without any data silos.
This quick read will introduce you to the concept of data cloud experience and how it works.
Data Cloud Experience Empowers Businesses
We’ve moved past the “cloud-first” period to a time where you can have your data engineering, data lakes, data warehousing, data science, data applications, and secure data sharing in one place.
What is the data cloud experience?
The concept of data cloud experience combines the ability to keep all your data and concurrent workloads under one platform.
This modern data architecture enables you with:
- Data Warehouse
- Data Lakes
- Data Engineering
- Data Exchange
- Data Applications
- Data Science
1. Modern Data Warehouse
Today majority of organizations, mostly like yours, want to become data-driven businesses and monetize their vast amounts of data. To commence their journey towards data modernization and monetization they need a composite data model to handle their complex processes.
Snowflake offers a unique architecture and near-zero management with its modern data warehouse. This “pay-for-what-you-use” model gives you the ability of decoupling compute resource scaling from storage resources, processing complex queries in a flash. It is widely acknowledged for its non-disruptive scaling, making it a manageable solution for organizations on a tight budget.
2. Augmented Data Lakes
Modern-day enterprises usually receive data from disparate data sources that stresses data teams to consistently extract, transform and load data and derive insightful information. Such insights don’t offer any real value unless managed strategically, especially to obtain analytics.
With Snowflake data lake, you can create a repository of unstructured and unprocessed data and store raw data in its native formats. Additionally, Snowflake enables rapid data access, query performance, and has built-in Data Access Control (DAC) and Role-based Access Control (RBAC), Governing and monitoring data access security efficiently.
3. Integrated Data Engineering
Under data engineering, raw data gets transformed into insights for making data-driven business decisions. There are various stages of data engineering, which include – data acquisition, ingestion, data cleansing, and restructuring.
Using Snowflake, data engineers can ingest, transform, and deliver data faster with deeper business insights. They just need to invest little to no time in architecture management, eventually, eliminating unnecessary operations such as capacity planning and concurrency handling. The platform enables professionals to put their efforts where they are actually needed.
4. Secure Data Exchange
Data exchange is the practice of sharing selected elements in a database or data storage of an account with other account holders. It is imperative that data exchange must be done confidentially and with utmost security.
Snowflake for data sharing equips businesses with the desired control and governance over data security. Being responsible for data exchange in Snowflake, you get the ownership of determining who sees what data, and which business units and partners get access to the secured copy of your data. You can monitor data usage and control multiple workflows.
5. Agile Data Application Development
Businesses need a robust platform that can eliminate data bottlenecks and provide secure data for application development pipelines. The platform should be able to scale cost-effectively for building massive data applications without operational burdens.
Snowflake data cloud possesses crucial features that can simplify data pipelines and improve overall engineering efficiency. It can also handle the infrastructure complexity effortlessly.
6. Advanced Data Science
Businesses have their strategic processes and algorithms in place to extract knowledge and insights from both – structured and unstructured data. The knowledge obtained can then be converted into actionable insights and used to make pivotal business decisions.
Snowflake empowers you to accelerate your operational workflows with incredible data processing power. It minimizes the time spent on requesting data access by putting a single point of access to a global network.
Take Your First Step Towards Data Cloud Experience with Snowflake
To summarize, adopt Snowflake for its efficient data ingestion, transformation, security, analytics, and visualization. If you’d like more information on Snowflake, even to migrate to this advanced platform or to build it from scratch, you can always contact us.