SNOWFLAKE – THE CLOUD DATA PLATFORM BUILT FOR ANY USER, ANYWHERE

The value of Snowflake for business

Snowflake combines the power of data warehousing, the flexibility of big data platforms and the elasticity of the cloud at a fraction of the cost of traditional solutions.

Snowflake is a cloud-first data warehouse built from the ground up for the cloud and for today’s data and analytics landscape. It takes the complexity out of running a data warehouse whilst providing significant performance and cost advantages over traditional data warehousing solutions.

The Snowflake architecture allows storage and compute to scale independently, so customers can use and pay for storage and computation separately. The sharing functionality makes it easy for organisations to quickly share governed and secure data in real time.

Why do businesses want to move to Snowflake Data Cloud Platform?

Snowflake enables the business to:

  • Invest their focus on data by just simply loading data to Snowflake; it is ready to consume with no additional overhead like traditional data platforms.
  • Share live data securely across your organisation or to external organisations, in a simple yet powerful SQL interface.
  • Reassuring query performance across workloads, unrivalled by existing on-premise data warehouse solutions.

How can intelia help?

Enterprise Data Strategy
Define where you want your data to take you. We help develop your enterprise data strategy to articulate your journey and enable you to achieve your data vision, goals and objectives.

Data Integration and Automation
intelia’s experienced data integration consultants excel in the consolidation of disparate on-premise and cloud data sources via a variety of tools, methodologies and data modelling techniques, that adhere to industry best practice.

The New Age of Data Sharing
The traditional way of sharing data through files and complex ETL processes is a thing of the past. intelia’s experienced consultants can guide organisations through modern and innovative ways of data sharing with external parties.

Engineer Your Snowflake Solution
Our experienced team can help you implement, integrate and automate Snowflake. We provide data engineering, migration and data consolidation; one place to ingest and consume data, means one place to monitor and measure data.

Managed Support Services
We don’t simply press install and leave. Our team are ready to support your organisation through a diverse range of managed services.

Let intelia guide you on your Snowflake implementation journey.

Get in touch with intelia

intelia has a team of Snowflake certified consultants and technology leaders who can help you with your Snowflake implementation journey, no matter what stage you are at.

Get in touch with intelia

With a key emphasis on scale and data sharing, Snowflake can significantly accelerate your data strategy.

Centralised data management serves as a data lake and data warehouse

Unique architecture separates compute from storage

Ease of use with cloud scale and performance at an instant

Cross-organisation data sharing

USE CASE: QUERY PERFORMANCE

As enterprises rise to the age of analytics, more business users are utilising self-service analytics at their fingertips, where the latest insights are needed at speed of thought.

Current on-premise data warehouses produce bottlenecks, lack optimisation and prioritisation of queries, resulting in data driven organisations unable to access timely insights.

Analytics queries may sometimes take several hours, if not days, competing with other concurrent users and workloads that utilise the same compute resources.

Read more - Performance and scalability using Snowflake

USE CASE: MAINTENANCE AND OVERHEAD

As volumes and variety of data continues to increase, so does the complexity of maintaining data on traditional data platforms. Cumbersome maintenance activities, with a vast array of resources for frameworks such as HADOOP, creates overly complex and costly data environments.

Resources required in ageing data platforms include; data engineers, full stack programmers, solution architects and platform engineers across multiple ecosystems, in most cases with a mix across on-premise and cloud infrastructure. Technical complexities include partitions on your Hadoop file system and file maintenance; moreover, data engineers are constantly challenged with indexing, partitioning and collecting statistics for tables within your data warehouse.

Legacy on-premise data platforms required outdated maintenance activities, where backup to file or tape are cumbersome for data restoration and may take days if not weeks.

These factors affect the downtime of a data platform, which have become mission-critical in modern data driven businesses.

Read more - Reduced Maintenance and Overhead

USE CASE: PARTNER DATA SHARING

There’s an increasing requirement to deepen insights by utilising more third-party data. Traditionally, this has been performed via file sharing and Extract Transformed Load (ETL) processes within an organisation’s file system to external parties. Traditional data sharing delivery mechanisms include emails, File Transfer Protocol (FTP) and ETL.

As of late, many organisations have moved to sharing via the cloud, where barriers still exist in terms of providing near real-time insights and value from disparate data.

Current on-premise data sharing architectures administer a high degree of network security, file system maintenance/overhead, and limited analysis of data sharing from business to business. These processes are slow, cumbersome, costly and resource intensive, and only allow for moving limited amounts of shared data.

Read more - Partner Data Sharing Enablement

USE CASE: COST REDUCTION AND SIMPLIFICATION

As organisations invest in their data infrastructure, as well as their platforms and tools, the complexity, maintainability and cost control become unmanageable.

For example, a single organisation may have a mixture of on-premise and cloud storage with HADOOP clusters for unstructured data processing, as well as a SQL data warehouse with curated structured data marts.

Read more - Cost Reduction and Simplification