Migrating from Teradata to Snowflake – the Right Move for the Right Cloud Platform

There isn’t any apparent reason why your organization should still be reliant on technology from 1979. It goes without saying that there is a Teradata data warehouse appliance in your data center, probably even two for that matter. However, aside from approving its purchase, chances are you are unaware of why exactly your company has more than one of this 10-million-dollar solution.

For close to 40 years, Teradata’s method of employing multiple microprocessors specifically designed for decision support. The idea was that several microprocessors would be harnessed to pull the load of enormous amounts of enterprise data instead of a single microprocessor. This was up until 2012 the only conceivable means of accurate and secure enterprise-wide data storage, since the very same year saw the emergence of Snowflake.

Snowflake computing played a critical role in bringing about a paradigm shift in the way we use data and store data. It designed the very first and only data warehouse designed specifically for the cloud, as opposed to an expensive data center limited solution. Snowflake offered a superior and cost-effective solution with a striking differential. 100 dollars’ worth of Snowflake cloud data warehouse resources can deliver the data processing resource equivalent of 10 million dollars’ worth of Teradata’s data warehouse solution.

Here are five more reasons why your organization should make the switch from legacy cloud platforms such as Teradata to more advanced one’s such as Snowflake.

1. Snowflake Enables a Single Source of Truth

We can define a single source of truth as one unifying source that is absolutely discreditable and accurate to the tee. Teradata provided a sufficient enough solution to see to this in the past, but with a boom in digital innovation and its subsequent explosion in data volumes, Teradata found it could no longer cope. The resulting aftermath was a fragmented data landscape dotted with a multitude of data repositories. With Snowflake you can store all of your data in a single place – a data warehouse built for the cloud. In this way your organization can benefit from a single data source to utilize for all business processes. Leverage decision making based on accuracy with the help of Snowflake’s single source of truth.

2. Economize on Data Warehouse Costs with Snowflake

The ten-million-dollar expense incurred by Teradata doesn’t end there. Following up on its installation requires software licensing, hardware maintenance, data center space and so on. The Total Cost of Ownership (TCO) of Teradata continues to expand as it begins to impose demands on your extant IT capabilities and resources. Snowflake comes with a unique pricing strategy contrary to the one in use by Teradata. Your organization can pay for Snowflake’s cloud computing resources alone on a per-second consumption basis.

There is a level of elasticity that comes with Snowflake you cannot achieve with Teradata – Snowflake allows you to access any level of computing prowess as and when required whilst paying for that extended exertion in isolation. In this manner your organization can avoid over paying for unnecessary warehouse power.

3. Snowflake is Equipped with Impenetrable Security

Breaches in data are a very serious threat and pose a number of dangers to an organization. Assets that have taken years to build such as trust, customers and money can be lost in a matter of a few seconds. The year 2018 alone saw the loss of 3.35 billion records either lost or stolen due to a breach in data warehouses.

Snowflake’s core offering is a cloud-built data warehouse. This means that securing the data which it houses its number one priority and the design of the platform has been centered around this very purpose alone. Implementing a range of world-class practices and technology supported by industry security certifications Snowflake takes every effort possible to keep customer data safe. Here are some of Snowflake’s security measures –  

• Safe Data Transmission: All data is encrypted in transit with best-in-class encryption.
• Access Control & Authentication: Data access only possible through multi-factor authentication.
• Data Integrity Measures: Snowflake data is restored to its previous state on demand and in response to accidental or intentional deletions.

4. Snowflake can be Scaled with Ease

Upgrading the capacity of a traditional on-premise data warehouses like Teradata can prove to be expensive as well as cumbersome, not to mention time-consuming and inefficient. This is because when solutions reach their computing capacity, workloads and users are left in long queues making real time scalability much more difficult than initially expected. Snowflake on the other hand was built for the cloud with performance and disruption-free scalability, this is because:

• Snowflake is an independent yet logically integrated storage and compute. This means that one can be increased without having to increase the other.
• Virtually-unlimited concurrency. In order to meet SLAs a selective compute cluster can be selected for each workload. This translates into the ability to scale to as many concurrent workloads as required.
• Disruption free instant scalability. Teradata is either underutilized or collapsing under the strain of growing workloads. Snowflake however can scale up and down without any hinderance.

5. Snowflake Comes with Advanced Analytics

Data-driven organizations are fast becoming the future. Since Artificial Intelligence (AI) and Machine Learning (ML) require unlimited access to massive amounts of data, one could say the time is ripe for implementation. Workloads of this scale would cause Teradata to crumble. Snowflake on the flipside can instantly cater the compute power required to process such monumental data loads. Snowflake cloud-constructed data warehouses can afford a reliable base from which to explore avenues in which AI can benefit your organization.

DataSwitch provides intuitive, predictive and self-serviceable schema redesign from traditional model to modern model with built in best practices, as well as fully automated data migration & transformation based on redesigned schema and no-touch code conversion from legacy data scripts to modern equivalent. DataSwitch provides self-serviceable, business user friendly, metadata based, providing AI/ML driven data aggregation and integration of poly structure data including unstructured. It consolidates and integrates data for domain specific data applications (PIM, supply chain data aggregation and etc.). DataSwitch also provides intuitive, no code, self-serviceable, conversational AI driven “data as a service” and is intended for various data and analytics consumption by leveraging next Gen technologies like micro services, containers/Kubernetes.