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One Six Solutions Reaches Snowflake Premier Partner Status

One Six Solutions Reaches Snowflake Premier Partner Status

Published

January 20, 2022

Snowflake

One Six Solutions is excited to announce our latest achievement: reaching Snowflake Premier Services Partner status! This achievement recognizes One Six Solutions and Snowflake’s strong partnership, and the success we have delivered for our customers on their Snowflake projects.

As experienced Snowflake Premier Services Partners, we have helped an array of companies across size and industry, achieve better business outcomes with Snowflake. Whether you are just getting started with Snowflake, looking to migrate from a legacy data platform, or need help implementing Snowflake as part of your modern data stack, One Six Solutions’ Snowflake consulting services will guide you through every phase of the project.

Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the Data Cloud.

If you would like to learn how One Six Solutions can help with your Snowflake or Data Warehouse project, schedule a FREE Consultation with us today.

Why a Cloud-Based Data Architecture Is the Right Choice for Your Healthcare Organization

Why a Cloud-Based Data Architecture Is the Right Choice for Your Healthcare Organization

Published

July 10, 2021

Data & App Engineering
Healthcare & Life Sciences
Tableau
Power BI
Fivetran
Matillion
Snowflake

Patient demand for access to personal health data continues to increase while healthcare organizations strive to provide improved patient outcomes. At the same time, they are facing budget constraints, interoperability issues and privacy regulations. The Health Information Portability and Accountability Act (HIPAA) regulates how healthcare organizations update such accessibility, keeping data safety and integrity at the forefront.

Cloud-based data architecture improves the healthcare experience for both patients and healthcare organizations. Incorporating cloud-based applications and services as part of your healthcare organization’s data architecture can help improve patient access while following HIPAA laws. Cloud-based healthcare applications also save your team time and money, simplifying the approval process.

One Six Solutions brings these solutions to your healthcare organization with a modern, cloud-based data architecture.

Reduced costs and improved scalability

With large quantities of patient and company data coming from a multitude of sources, a cloud-based system allows your company to operate at scale and at budget.

Trying to guess the correct number of servers as well as other hardware and software needs for your organization are time-consuming and costly. A cloud data warehouse meets all of your organization’s data needs now and into the future. It allows you to scale your storage and computing power to meet your needs within minutes.

Cloud computing allows your healthcare organization to pay for the storage and services you need now, rather than continuing to struggle with legacy technology. In partnership with One Six Solutions, you ensure that your organization has the latest technology at its fingertips without incurring a greater spend.

Incorporating cloud-based applications and services also saves your team time and money by freeing your IT employees of tedious tasks such as tending to and upgrading in-house servers and deploying updates.

A simple, yet powerful cloud data warehouse such as Snowflake provides a fully managed, pay-as-you-go service that is secure. Financially, the costs are based only on the storage and compute you use.

Interoperability across the organization

Your healthcare organization’s interoperability depends on the movement of data from source systems to a centralized location for holistic analytics. Today, because of the cost-effectiveness and power of the CDW, data transformations can happen after the data is fully replicated from the source to the warehouse on a repeatable schedule by leveraging tools like Matillion.

Today’s cloud-based products provide faster and more robust capabilities for your organization than connectors custom built by consulting firms or in-house developers. With a few clicks of a button, platforms such as Fivetran or Matillion’s Data Loader provide full data replication of a wide array of applications and databases into a cloud data warehouse.

Equally important, cloud-based patient data provides interoperability with your organization’s external partners such as pharmaceutical companies, insurance claims and payments. A cloud-based approach allows information to flow seamlessly between individuals and organizations that require access to it while still protecting its sensitive nature. Therefore, healthcare delivery improves and becomes more efficient in the cloud.

Faster time to insight

Whether it is Tableau, Power BI, Qlik Sense or any number of tools in this space, cloud offerings provide a fully managed instance for a single browser-based access point for dashboards and reports.

Improved patient outcomes

One of the most important measures of healthcare is the final outcome. Patients seeking to improve that outcome require on-demand access to their healthcare information to make better life decisions.

If you’re interested in migrating your healthcare organization’s data to a personalized, cost-saving and safe platform, contact us for additional information. The team here at One Six Solutions has worked with a wide array of technologies in the healthcare data world. Our goal is to design and build an architecture that works best for you based on your organizational and business needs. Let us know how we can help.

My Snowflake Crushed Your Cube!

My Snowflake Crushed Your Cube!

Published

March 22, 2021

Data & App Engineering
Snowflake

We’re seeing a lot of activity with clients nowadays eager to modernize their data platforms. This post discusses an architecture option that is gaining more traction with some of our clients as they attempt to get their feet wet with modern data platforms leveraging tools like Snowflake and Fivetran.

We see it all the time, our clients know that they have one or all of the following problems with their existing data platforms: 

1. Query response times are too slow.

2. One group of users or reporting applications bring the platform to its knees.

3. Business rules and data transformations will be too hard or too costly to completely re-write on a new platform.

The good news here is that modern data platforms utilizing technologies like Snowflake and Fivetran can solve these problems.  Consider a typical legacy data architecture below:

What if one can reap the performance, elasticity and security benefits of a cloud Data Warehouse like Snowflake with minimal impact on their existing platforms?  Granted, anyone out there can find a reason why this solution doesn’t work for 100% of use cases, but we’re seeing this method become increasingly popular as a first step in modernizing data platforms.  Now, let’s see how a relatively simple technology switch in the diagram below can make a big impact.

Let’s talk through the problems addressed above one by one now:

1. Query response times are too slow – In the new world, our reports and dashboards are now pointing directly to Snowflake.  We can leverage its on-demand elasticity where necessary but simply moving your data to Snowflake will result in drastic performance improvements over classic RDBMS platforms and/or legacy OLAP tools.  Opportunities to scale out Snowflake on-demand can increase performance an order of magnitude in many cases.

2. One group of users or reporting applications bring the platform to its knees – here lies the beauty of Snowflake’s Virtual Warehouses.  Outside of the platform itself simply being more performant you now have fine control over which users or applications can utilize what processing resources a.k.a. Virtual Warehouses.

3. Business rules and data transformations will be too hard or too costly to re-write on a new platform – Often, too much time and money has been spent on the current architecture so a wholesale re-write may never make it past leadership. The good news here is that we can keep the existing architecture in this new world.  Continue to leverage your data staging, cleansing and Data Warehouse processing logic.  Don’t worry about changing ETL tools or re-writing business rules.  Let’s not re-test everything that has been already tested and validated.  If it’s working today, don’t fix it.  Simply replicate your legacy Data Warehouse to Snowflake using a modern, flexible data pipeline like Fivetran.  As changes to data occur (both to the data itself and/or the data structures) products like Fivetran are smart enough to automatically replicate those changes downstream to Snowflake as frequently as you would like.

In the new architecture, data remains fresh, data pipelines don’t break when new columns or tables are added to your Data Warehouse and data consumers have the performance and reliability they need from their analytics tools.  Now they can spend more time making decisions and less time waiting for reports and dashboards to refresh.  Let’s not forget existing reporting platforms pointing at legacy cubes or data marts would need to re-point to Snowflake which can take some time.  We suggest picking out the worst performing to start and slowly migrate as it makes sense.  Some clients choose only to write new reports against this new architecture after moving over the poor performers.

There are several approaches you can take to help modernize your data platforms.  We work with our clients every day to help them solve their biggest data challenges while providing alternate approaches that can save time and money.  If you are having challenges with your existing data platform, give us a call, we’d love to help!

Mike Galvin is a Co-Founder at One Six Solutions in Chicago and has over 20 years of experience assisting clients across various industries think through their toughest data challenges.  Mike can be reached at 312-761-1616 or via email at mike.galvin@onesixsolutions.com.

Six Features That Make Snowflake A Different Cloud Data Warehouse

Six Features That Make Snowflake A Different Cloud Data Warehouse

Written by

Jacob Zweig, Managing Director

Published

August 26, 2020

Data & App Engineering
Snowflake

Snowflake’s Cloud Data Platform is one of the go to tools for companies looking to upgrade to a modern data architecture. We commonly have clients ask about Snowflake, and what are the features that make it standout from other cloud data warehouse solutions, such as Amazon Redshift or Azure Synapse. In this article we discuss six distinctive and noteworthy features of Snowflake that make it different.

Cloud Provider Agnostic

Snowflake is a cloud agnostic solution. It is a managed data warehouse solution that is available on all three cloud providers: AWS, Azure and GCP, while retaining the same end user experience. Customers can easily fit Snowflake into their current cloud architecture and have options to deploy in regions that makes sense for the business.

Scalability

Snowflakes multi-cluster shared data architecture separates out the compute and storage resources. This strategy enables users the ability to scale up resources when they need large amounts of data to be loaded faster, and scale back down when the process is finished without any interruption to service. Customers can start with an extra-small virtual warehouse and scale up and down as needed.

To ensure minimal administration, Snowflake has implemented auto-scaling and auto suspend features. Auto-scaling enables Snowflake to automatically start and stop clusters during unpredictable resource intensive processing. Auto-suspend, on the other hand, stops the virtual warehouse when clusters have been sitting idle for a defined period. These two concepts provide flexibility, performance optimization, as well as cost management.

Concurrency and Workload Separation

In a traditional data warehouse solution, users and processes would compete for resources resulting in concurrency issues. Hence the need for running ETL/ELT jobs in the middle of the night when no one is running reports. With Snowflake’s multi-cluster architecture, concurrency is no longer an issue. One of the key benefits of this architecture is separating out workloads to be executed against its own compute clusters called a virtual warehouse. Queries from one virtual warehouse will never affect queries from another. Having dedicated virtual warehouses to users and applications provides the possibility to run ETL/ELT processing, data analysis operations and reports without competing for resources.

Near-Zero Administration

Snowflake is delivered as a Data Warehouse as a service (DWaas). It enables companies to setup and manage a solution without significant involvement from DBA or IT teams. It does not require software to be installed or hardware to be commissioned. With modern features such as auto scaling, both increasing the virtual warehouse size as well as increasing clusters, gone are the days for server size and cluster management. Since Snowflake supports no indexes there is no need for tuning the database or indexing the tables. Software updates are handled by Snowflake and new features and patches are deployed with zero downtime.

Semi-Structured Data

The rise of NoSQL database solutions came from a need to handle semi structured data, typically in JSON format. To parse JSON, data pipelines needed to be developed to extract attributes and combine those attributes with structured data. Snowflake’s architecture allows the storage of structured and semi structured data in the same destination by utilizing a schema on read data type called VARIANT. The VARIANT data type can store both structured and semi structured data. As data gets loaded, Snowflake automatically parses the data and extracts the attributes and stores it in a columnar format. Hence eliminating the need for data extraction pipelines.

Security

From the way users access Snowflake to how data is stored, Snowflake has a wide array of security features. You can manage network polices by whitelisting IP addresses to restrict access to your account. Snowflake supports various authentication methods including two-factor authentication and support for SSO through federated authentication. Access to objects in the account is controlled through a hybrid model of discretionary access control (each object has an owner who grants access to the object) and role-based access control (privileges assigned to roles which are then assigned to users). This hybrid approach provides significant amount of control and flexibility. All data is automatically encrypted using AES 256 strong encryption and is encrypted in transit as well as at rest.

These are not the only reasons why Snowflake is different. There are other features that standout, however these are the ones we have seen our clients benefit from the most. Snowflake should be considered as a solution for any business migrating to a cloud Data Warehouse. One Six Solutions is a Snowflake partner and has implemented Snowflake Cloud Data Platform solutions for clients looking for a modern data architecture platform.

OneSix is a Premier Snowflake Partner

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A Modern BI Primer (And Why Less is More)

A Modern BI Primer (And Why Less is More)

Published

March 5, 2020

Data & AI Strategy
Tableau
Power BI
Matillion
Snowflake

With a data technology landscape that is ever changing, it is at times a challenge even for technology firms to sort through the latest key terms and platforms that pervade the marketplace, each touting its advantage over the status quo. How much more a challenge, then, for organizations where technology is not their primary expertise? From a myriad of choices to build a modern data architecture for a competitive edge, what must companies buy and leverage to start or pivot their data journeys?

This primer is intended to educate a growing number of clients we see in the Small and Medium-Size Business (SMB) segment who are looking for a good framework to consider as they think through their future data capabilities.

So what makes a business intelligence (BI) or data architecture? And what do we mean when we say less is more as it relates to this architecture? Regardless of the technology stack that eventually gets approved and implemented, our team at One Six likes to speak of tools and platforms in terms of four big buckets:

Data Acquisition

What is it? This bucket is the piece of the architecture where we consider the movement of data from source systems to a centralized location for holistic analytics.

Why less is more: There are products in this space today that frankly provide faster and robust capabilities for clients than connectors custom built by consulting firms or in-house developers. With a few clicks of a button, platforms such as Fivetran or Matillion’s Data Loader provide full data replication of a wide array of applications (e.g., Salesforce, Google Ads) and databases (e.g., SQL Server, MongoDB) into a cloud data warehouse. Fivetran, in particular, detects changes to the source system automatically and moves data over seamlessly. Subscribing to managed services by leaders in this space means less maintenance activities for your internal IT group and more time to focus on value-added tasks downstream.

Data Warehouse

What is it? Whether you hear terms like data lake, data warehouse, or data lakehouse, here we are discussing a part of the architecture that stores information from disparate systems for historical, current, or forecasted analyses.

Why less is more: Rather than trying to estimate the right-sized on-premise hardware and software that is required to house all current and future data, consider a cloud data warehouse (CDW) that scales storage and computing power up and down as you need within minutes. Unless you are an organization at the scale of Netflix or Airbnb, a complex architecture is not necessary. A simple yet powerful cloud data warehouse like Snowflake provides a fully managed, pay-as-you-go service that is secure and costs are based only on the storage and compute you use. Again, less burden on your internal team, and more flexibility to build the structures you need to analyze your data efficiently. Plus, as your company grows and data volume grows as a result, the CDW can grow with you.

Data Transformation

What is it? When it comes to data, there have always been and will still be a need to clean, wrangle, and structure data in a way that makes sense for reporting. This bucket relates to the architecture piece where this transformation takes place.

Why less is more: Putting this as the third bucket is intentional. In the old world, a separate staging server was required to process data transformations prior to loading into a data warehouse. In addition, not all data from the source moved to the data warehouse due to cost of storage and compute. Today, because of the cost effectiveness and power of the CDW, data transformations can happen after the data is fully replicated from the source to the warehouse on a repeatable schedule by leveraging tools like Matillion. This means the transformations happen in the data warehouse itself so you can remove the maintenance and costs of a staging server. Even more, the low cost of storage allows the data warehouse to have all data from the source system immediately available for any changes to reporting needs.

Data Analytics

What is it? This bucket is the most visible component to a BI or data architecture. Here we are looking at product capabilities for building standardized dashboards as well as ad-hoc analyses that will be consumed by a wide audience in an organization.

Why less is more: Whether it is Tableau, Power BI, Qlik Sense, or any number of tools in this space, cloud offerings provide a fully managed instance that provides a browser-based, single access point for dashboards and reports. Less management and increased accessibility. In general, while each tool has its advantages, we continue to see tools moving towards parity. Here, a data governance strategy is key is reducing the number of data sets and reports while promoting the reusability of well-structured, certified data sets. This reusability increases the trust of the data and also empowers business users to find answers to questions on their own not found in standardized dashboards. And with tools like Ki and DataRobot that can augment established BI tools with its artificial intelligence and machine learning capabilities, we see increasing ways for analysts to solve business problems that we can provide guidance on.

Final Thoughts

So there you have it – Data Acquisition, Data Warehouse, Data Transformation, Data Analytics – four big buckets to easily see what you need to consider in a modern BI architecture. We hope that this modern BI primer has been helpful as you take the next steps into your organization’s data journey. Please note that the above technology platforms listed were used as examples only. The team here at One Six Solutions works with a wide array of technologies in the data world. Our goal is to design and build an architecture that works best for you based on your industry and business needs. Let us know how we can help.