The world is experiencing a major digital revolution triggering a significant rise in global data volumes. According to International Data Corporation, worldwide data will have expanded by 61% to 175 zettabytes by 2025, with cloud housing as much as data centers. Unstructured data amounts to 70% to 80% of the data generated today, and it is expanding beyond our imagination.

With the massive amount of data growth,  there is a growing demand for advanced analytics, insights, and predictive data models essential for organizations to become savvy enterprises. While the legacy system is an excellent technology, it was developed for relational data. Challenges with the current Legacy infrastructure, combined with an increased demand for cloud services, have created the perfect storm, driving a migration of legacy systems to the cloud

Along with the lack of an agile cloud data warehouse, the high cost of data warehouses is a significant problem. Snowflake storage costs around $1 per day per terabyte. With solutions like Teradata, you must pay not just for storage but also for computing power. Storage and other extras might cost as much as $10,000. This difference in value rises when time and other resources saved by utilizing Snowflake are included.

Snowflake has rapidly become the dominant cloud data storage solution. They distinguish itself from on-premises warehouses and its competitors by maximizing the cloud’s storage capacity. A prime illustration is analytics. The field of analytics has gotten more fragmented during the past two decades. This produced a need for a structure that combines the flexibility of the cloud with the traditional schema of data management and the complete SQL capabilities. Snowflake took into account all of these criteria and packed an excellent product. They merged the most advantageous aspects of on-premises hardware with the cloud’s flexibility, scalability, and consumption-based pricing.

Snowflake’s capabilities have been attracting an increasing number of Teradata clients. Snowflake customers have less oversight because of the intuitive and automated data compression, statistics collecting, workload management, concurrency of queries, and disaster recovery capabilities. Solutions like Teradata are more dependent on the DBA, necessitating more work and maintenance.

Why are On-Premises migrating to Snowflake?

Efficiency and speed

If you wish to load data more quickly or perform a large number of queries, you can ramp up your warehouse to make use of more computational resources due to the elastic nature of the cloud. After that, you can reduce the size of the virtual warehouse and pay just for the period you utilized.

Assistance for structured and semi-structured data

You may mix structured and semi-structured data for analysis and put it directly into a cloud database without first converting or transforming the data into a relational schema. Snowflake automatically improves the storage and querying of data.

Simultaneous access 

When too many queries compete for resources in a typical data warehouse with a high number of users or use cases, concurrency issues (such as delays or failures) may arise. Snowflake handles concurrency difficulties with its innovative multicluster architecture: Queries from one virtual warehouse have no effect on queries from another, and each virtual warehouse may expand as necessary. Data analysts and data scientists may get the data they want immediately, without having to wait for other loading and processing activities to finish.

Free-flowing data sharing

The design of Snowflake facilitates data exchange between Snowflake users. It also enables enterprises to share data with any data consumer, regardless of whether or not they are Snowflake customers, via reader accounts that can be created straight from the user interface. This feature enables the provider to establish and maintain a Snowflake profile for a user.

Usability and safety

Snowflake is spread across the network segments of the platform on which it operates — AWS or Azure — and is designed to function constantly and endure component and network failures with minimum damage. It is SOC 2 Type II certified, and extra degrees of security are available, such as compatibility for PHI data for HIPAA clients and network-wide encryption.

Other features include

• Automated features that require minimal to no human intervention.
• Cost is reduced as exponential value increases
• Flexibility, adaptability, and cost depending on usage
• Instead of establishing a 3rd party API connection, many partners and ELT products only need a plugin.
• Snowflake has made cloud migration easier than ever

Make the migration to the cloud easier than ever with DataSwitch!

The moment has come for enterprises to capitalize on this paradigm shift as the world rapidly evolves towards digital transformation. If you’re still devoting at least 40 percent of your IT budget to license fees for legacy systems, it’s time to simplify your costs and adopt a time- and cost-effective solution to your data problems.

Here is where DataSwitch comes into play.

Our clients’ migration to the Snowflake Data Platform is accelerated with the help of our intelligent tools and processes, as well as our combined experience. We recognize the purpose of stored procedures and have developed functionality that is vital to Snowflake. We have your back for everything from script conversions to migration planning, data migration, and data ingestion.

Why choose DS Migrate?

Intelligent assessment & evaluation: We conduct an in-depth volumetric analysis of the source architecture (legacy system) and usage pattern of the data platforms to assess the data complexities and align them with Snowflake’s infrastructure. Usage pattern consists of measuring data in and data out, no.of users logged in, no.of applications using the platform. Experts at DataSwitch conduct usage analysis (6-8 weeks) based on log files to segregate data as “hot” (needed immediately) and “cold” (not needed immediately).  The analysis report contains information on Space consumption and utilization, CPU & I/O utilization, Date range analysis, User analysis, etc. With this customers can take maximum advantage of the cloud system to reduce the cost and efforts of migration. The good news is – Cloud-based technology solutions like Snowflake enable IT operations to become an operating expenditure (OpEx) rather than a capital expense (CapEx), eliminating the need for large initial investments and replacing them with predictable monthly fees. We also conduct PoT (Proof of Technology) to understand multiple parameters like performance, time taken to load the data, and other factors that can lead to maximum efficiency.

Smart Schema Re-design: Say goodbye to complicated ‘Schema structure’ and say hello to an easy-to-use, intuitive, and self-serviceable automated schema redesign. It has a drag and drop option to redefine the schema by introducing business rules that support smart and seamless operations.

There are 3 types of Schema redesign we offer:

• As-Is (Lift & Shift migration)
• Re-platform (Change of Technology & Infrastructure)
• Re-Engineering/Re-Architecture (Change of Technology, Infrastructure, and underlying Data Structure)

No Touch Data Migration: Automate the entire data migration process from legacy to Snowflake and say no to manual intervention using a simplistic drag and drop UI. This reduces complexity and boosts productivity while enhancing the efficiency of the process. DataSwitch specializes in high-volume data extraction through bulk export processes. We implement highly efficient Spark-based tools to carry out transformations required during migration. The entire operation will be highly secure and effective and close to the native format. Re-pointing of data from source to target system (Snowflake) will be managed by DS Migrate for both historical as well as incremental needs. For the historical conversions, DS Migrate leverages FTP method & for the continuous/live sync up of the data in real-time, DS Migrate leverages CDC streamer & CDC live merge.

Automated Data Validation: DataSwitch uses an in-built tool called ‘Data validator’ to compare the data from the source system to the migrated Snowflake system. This tool compares data cell-cell, row by row, and column by column to ensure that all the data has been successfully converted and there is no data loss.

Seamless process conversion:  Convert your legacy data scripts and ETL tools to Snowflake using DataSwitch’s “No-Touch Code” easy online interface. We provide tool-to-tool, script-to-tool, a tool-to-script, or script-to-script translations as well. We conduct this process irrespective of the source systems. We support both methods of Snowflake – JS and SQL stored procedures. We also support migration from source systems to Snowpark (the newly introduced Spark-based version of Snowflake)

Code to Document: Earlier, the documentation had to be produced by the developers themselves. Thanks to the DS Migrate tool, the entire source code is transformed into Snowflake code seamlessly. Along with the code, you also get access to the documentation with metadata information, entity relationships, functionalities, Data Lineage, source-target mapping specifications, etc

Switch to the Cloud with DataSwitch