Snowflake: A revolutionary data warehousing experience
As we move ahead in a world which has become increasingly so uncertain, individuals, organizations, and companies are relying on data or in simple terms, “processed information’ more than ever to make even the smallest of decisions. It has become evident that the more we rely on data, more the data we will need.
As a matter of fact, in a survey conducted in 2018, it was concluded that Global DataSphere has reached approximately 18 Zettabytes which is equivalent to 109 Terabytes and we all know that this data will continue to increase.
Now, to utilize this data for making important business decisions, there needs to be some sort of data warehousing solution in place which can store large amounts of data, provide lowest possible latency, reduce overall costs, and finally provide a real time view of the data for its analysis, moderation, modification and curation.
There are traditional data warehouses present in the market which can hold extreme amounts of data and can perform the operations that we want, but it has always been challenging to find an optimal solution that balances the growing needs of
- Performance and speed
- Storage and support for structured and semi-structured data
- Concurrency and accessibility
- Seamless data sharing
- Availability and security
Image source: Snowflake
In 2012, the world was introduced to Snowflake which would go on to become one of the most sought-after data warehousing solution in the coming future. Snowflake offers a cloud-based data storage and analytics service, generally known as “Data Warehouse-as-a-Service”. It allows users to store and analyze data using cloud-based hardware and software. With the increasing demand Snowflake shook hands with Amazon S3 in 2014, with Azure in 2018 and with Google Cloud Platform in 2019, the Snowflake data exchange now allows customers to deliver, exchange and securely share data.
Since it is built on the top of cloud architecture, there is no hardware or software required to select, install, configure or manage which makes Snowflake the perfect candidate for organizations that don’t want to dedicate resources for setup, maintenance, and support for in-house servers.
Standing out from the crowd
One of the most important features that makes Snowflake different is its ability to provide flexibility by allowing users to pay only for the resources they use and to scale up and down as needed.
Snowflake recognizes storage and compute functions differently which means organizations that require high storage but need less CPU cycles, or vice versa, are not required to pay for an integrated bundle that requires them to pay for both. Thus, each of the Snowflake layers mentioned below are independently scalable.
Image source: Snowflake
Database storage layer:
The database storage layer holds all data loaded into Snowflake, whether it is structured or semi-structured. Additionally, Snowflake manages all the aspects of how data is stored including organization, file size, structure, compression, metadata, and stats.
The compute layer is made up of virtual warehouses that execute data processing tasks required for queries. Each virtual warehouse (or cluster) can access all the data in the storage layer, then work independently, so the warehouses do not share, or compete for, compute resources. This enables non-disruptive, automatic scaling, which means that while queries are running, compute resources can scale without the need to redistribute or rebalance the data in the storage layer.
The cloud services layer uses ANSI SQL and coordinates the entire system. It eliminates the need for manual data warehouse management and tuning. Services in this layer include:
- Infrastructure management
- Metadata management
- Query passing and optimization
- Access control
Neal’s journey with Snowflake
We at Neal Analytics are a team of bright and innovative minds with constant focus on right-sized and pragmatic approaches towards digital transformation. This mindset also enables us to leverage Agile methodologies and flexible engagement models to deliver measurable customer value and success. Flexibility as a key element for digital transformation, and it’s become even important organizations looking to seize the benefits of a cloud-based data warehousing solution to capture superior analytics. A flexible model also helps organizations take advantage of pay-as-you-go pricing, an advantage that is for companies who are steadily becoming more data-driven by migrating their data and systems to the cloud.
Even pioneers in technology must continue to modernize. One of our customers, an American-based supplier of health information technology services, devices, and hardware, needed a solution to better manage the exponential increase of data. With their products used in over 27,000 facilities and offices in more than 20 countries, infrastructure optimization was key to remaining a competitive player in the field. The company’s on-premises solution, which supported them for nearly a decade, was becoming increasingly difficult manage for a variety of reasons including
- Exponentially increasing data and information
- The on-premises solution was not able to deal with the complexity and quantity of data received
- The infrastructure required for the system was not cost-effective, and it gained severe performance issues that would grow more difficult (and expensive) to manage over time
During our consultations, the company agreed that Snowflake would be the optimal database for their needs. We developed a 4-step modernization strategy to help the customer move their data and systems to Snowflake based in Microsoft Azure by building solution that gave them control over multiple factors such as:
- Resource utilization
- Low-latency based solution
- Modernized data for better analytics
- End-to-End cloud-based architecture that enabled them access to this vast data by performing activities such as Snapshot Creation, Transformation Logic Development, Data Modelling, Storage Strategies, Visualization and finally dig insights out of this data.
With examples like above, there are many successful customer stories that we have been able to achieve using Snowflake and data warehousing on the cloud, as well as our sheer will to comply with the designed strategy. Our data modernization roadmap helps us achieve solutions for the varied set of problem statements that customer faces, and with the increase of data-driven culture, it has allowed Neal Analytics to develop solutions that not only solves the customer problem statements, but rather innovates newer ways which allows customer to take a hold of these newly created architectures with ease.
Using Snowflake and data warehousing to seize new opportunities:
If we take a moment to look at the impact of COVID-19 on the global data warehousing market, we will learn that it is expected to grow at a higher rate for the 2020-2025 forecast period. Increase in the need for dedicated storage systems for growing volume of data and need for low-latency, real-time view and analytics of big data are the major factors driving the growth of the global data warehousing. The data warehousing market is poised for a quantum shift, owing to factors such as ongoing demand for next-generation business intelligence along with increasing amount of data generated by organizations which is projected to accentuate data warehousing market growth over the forecast period.
A data-driven approach has never been more valuable to addressing the complex, yet foundational questions enterprises must answer. Data now supports decisions few executives thought they’d be making even 90 days ago. It helps business leaders understand fundamental information like their cash flow, and it’s also a guide as their business moves forward in this crisis (or future crises). Trusted data illuminates what is happening in your business and your business processes. It may even show you where your infrastructure and your critical systems need better support. Organizations that have good data management, data governance, and data intelligence practices are much better positioned to respond to challenges and thrive in crises. Moving your business-critical data to Snowflake’s cloud data platform gives you the agility and flexibility to adapt quickly, responding to new demands faster than your on-premises legacy platforms.
In addition to the impact analysis and understanding towards market trends, we at Neal Analytics are making sure that our success lies in a customer’s success. If we are able to develop a solution which is deemed on-par with the constantly changing market, it is also important to understand that several post-development activities such as Knowledge Transfer Sessions, Demonstrations, Documentation, Workshop, 24×7 support as a service helps the customer in understanding the solution that we have built for them and how they can fully utilize the potential of a developed solution.