The partnership between Io-Tahoe LLC and Snowflake Inc. represents an acknowledgement that the power of the cloud combined with intelligent automation is going to play a central role in the future of enterprise data management.

When it comes to data the needs are clear. Enterprises want data quality and a central repository where information can be accessed quickly at scale without the need for a lot of manual work.

The combination of Snowflake’s Data Cloud, where siloed data is united, governed and executed to serve diverse analytic workloads, and Io-Tahoe’s machine learning algorithms, which increase accuracy and speed in learning complex data relationships within an enterprise environment, offers a solution that is attracting customer interest.

“The resource that Snowflake can leverage here is the metadata,” said Ajay Vohora, chief executive officer of Io-Tahoe. “Working with Snowflake, we’ve enabled that intelligence to be gathered automatically, reducing that manual effort and putting that data to work. We’ve packaged this with our AI and machine learning specific to those data tasks. It made sense and that’s what resonated with our customers.”

Vohora spoke with Dave Vellante, host of SiliconANGLE Media’s livestreaming video studio theCUBE, and he was joined by Duncan Turnbull, partner sales engineer at Snowflake. Vellante also spoke with Glenn Grossman, enterprise account executive at Snowflake; Yusef Khan, head of data services at Io-Tahoe; Tiji Mathew, enterprise data solution architect at Io-Tahoe; Patrick Zeimet, enterprise data engineer at Io-Tahoe; and Senthilnathan Karuppaiah, solutions architect and head of production engineering at Io-Tahoe, in separate interviews.

The discussion, part of Io-Tahoe’s Data Automation Series “ActiveDQ Intelligent Automation for Data Quality Management” livestream event, included a focus on how Io-Tahoe partners with Snowflake to version data, the importance of data quality for enterprise operations, how one financial company is using analytics and pivoting to a new business model, and the vertical market opportunity realized by the two companies’ combined solution. (* Disclosure below.)

Watch the interview with Vohora and Turnbull below:

Maintaining the metadata push

What customers are responding to is an ability to leverage the features of both Io-Tahoe and Snowflake for the heavy lifting necessary to ensure and monitor data quality. Users define the “as-is” model by leveraging Io-Tahoe to profile various data sources and then push the metadata to Snowflake.

“We’ve seen a huge increase in the number of organizations interested in a Snowflake implementation for an innovative, precise and timely method to ingest their data,” Zeimet said. “We create a data catalog within Snowflake for a centralized location to document items such as source system owners, allowing you to have those key conversations and understand the data’s lineage, potential blockers and what data is readily available for ingestion. While you’re working through those key conversations, Io-Tahoe will maintain that metadata push and partner with Snowflake’s ability to version the data.”

It sounds fairly straightforward, but there are a number of challenges involved in achieving the kind of seamless data management state that organizations desire. Foremost among these issues is data quality.

The problem starts with a natural problem in many organizations. Data winds up in a lot of places, touched by a lot of hands. The key is to bring a singular focus to the information a company needs, recognizing that the work of many businesses is done in teams.

“These different teams are going to have slightly different or radically different answers to the same kinds of questions, which makes it hard for teams to work together on their different data problems that exist inside the business,” Turnbull said. “If you have a single scalable system for putting all of your data into it, you can sidestep a lot of this complexity and you can address the data quality issues in a single way.”

Inspection and transformation

The way that Snowflake addresses data quality is through a different take on the general process of copying data from one or more sources into a destination system. The common process is through extract, transform and load,or ETL.

“We take an inspection, which traditionally was ETL, but now in the world of Snowflake it’s really ELT,” Grossman explained. “We’re extracting, we’re loading and inspecting, and then we’re transforming out to the business.”

An important part of this process involves ensuring that bad quality data is quickly identified and prevented from flowing downstream. Io-Tahoe works with Snowflake to tag data elements based on the rules set by a customer’s data staff.

“With increased automation and fewer people, our machine learning algorithms augment the data pipeline to tag and capture the data elements into a comprehensive data catalog,” Mathew said. “As Io-Tahoe builds the data catalog across source systems, we tag the elements that meet the business rule criteria, while segregating the failed data examples associated with the elements that fall below a certain threshold.”

Communication plays a key role in maintaining data quality. Io-Tahoe and Snowflake provide a process to notify a customer’s data experts whenever questionable data is detected in the monitoring phase.

“The data governance team, along with enterprise architecture or IT, are involved in setting up the data catalog,” said Karuppaiah. “When it is in the monitoring phase, during a data incident or data issues, Io-Tahoe broadcasts data signals to the relevant folks to act and remedy it as quickly as possible.”

Watch the interview with Karuppaiah, Mathew and Zeimet below:

Building a new business

The model that Snowflake and Io-Tahoe have partnered to offer is attracting companies seeking to enter new business sectors through merger and acquisition. Io-Tahoe recently began working with a client in the financial services space that had grown over the course of the past 10 years by acquiring various companies. Each acquisition brought new datasets, applications and multiple CRM systems into the parent company. This particular client was looking to pivot the business toward management of cryptocurrency assets, according to Vohora.

“We migrated the relevant data into the Snowflake cloud platform, and it’s where we’re giving time back,” Vohora said. “The transition to mobilized data started with a clean slate to build upon a new business as a digital crypto asset manager along with the legacy traditional financial assets like bonds or stocks. It’s where we’re starting to see a lot of innovation.”

Vohora’s example demonstrates how the Snowflake-Io-Tahoe partnership is allowing businesses to pivot toward new models by addressing flaws inherent in legacy systems.

“Every migration to Snowflake is going to have a business case, and that’s going to be partly about reducing spend in legacy IT, servers, storage, licenses, support, all of those good things that CIOs want to be able to turn off entirely,” Kahn noted. “There’s confidence and trust. You can see chief data officers and CIOs have received demonstrable results, that they’ve been able to improve data quality across a whole bunch of use cases.”

Watch the interview with Kahn and Grossman below:

Io-Tahoe has seen that the application of automation and machine leaning processes has opened new doors into vertical markets. Data is the common denominator here, with the need to reduce time and improve efficiency in how critical business information is gathered and managed.

“The employment of AI and machine learning technologies specifically to those data processes, almost as a precursor to getting into marketing automation or financial information automation, that’s really where we’re seeing the momentum pick up, especially in the last six months,” Vohora said. “Of course, solving a problem, a customer’s pain point with technology, that never goes out of fashion.”

Watch the entire show below:

(* Disclosure: TheCUBE is a paid media partner for Io-Tahoe’s Data Automation Series “ActiveDQ Intelligent Automation for Data Quality Management” livestream event. Neither Io-Tahoe LLC, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Image: Pixabay