Services

For setup and onboarding, administrators are coached to set up a managed data lake, Liquify Reservoir, on top of Snowflake in as little as 3 months. The process is ongoing and self-validating as data streams into the system.

Companies can also upgrade their existing Snowflake data lake to a Liquify-managed reservoir.

Data owners set up, annotate and manage their own data from any data source.

Governance can put policies in place around data access and utilization before analysts or business users even join the platform, ensuring that sensitive data is always protected, and security and compliance is at the foundation of business analytics for your company.

The organization of Liquify Reservoir revolves around a master list of the subjects that are most important to the business; things that are at the heart of a company’s business that the entire company wants more insight on.

Liquify’s AnalyticsLab™ provides a customizable collaboration platform for business users who want to make insights part of every business day.  

On log in, users can:

• Quickly see what’s new
• Message their team
• Find their tasks
• Ask Ivy the Intelliguide for help

Liquify helps administrators to take advantage of the best of Snowflake by suggesting optimization options at just the right times.  

Liquify limits expensive queries. If a user’s computation is estimated to cost more than a certain amount, users will be assisted to collaborate with a technical resource to refine their query or to obtain permission from management and governance to execute a one-time analysis.

Two important aspects of Liquify’s Reservoir technology, SmartPartitions™ and SubjectInterlinks™, carefully organize data in the managed lake to optimize the data’s retrieval from Snowflake.  

As a result, AnalyticsLab™-generated queries are system-optimized to retrieve only the rows needed to satisfy analytics requests without scanning the disk!

The AnalyticsLab™ allows Governance to create and enforce policies on a global, business unit, workgroup or individual level.  

Governance has control over the sharing and publishing of expressions, derived expressions, and datasets.  

Governance can create AnalyticsLens – a series of filters and/or masks that can be applied to data, including personally identifiable information (PII).  

Liquify gives companies the ability to comply with Zero-Trust.

AnalyticsLab gives users the ability to upgrade derived expressions on an ongoing basis, improving analytics and eliminating bias and mistakes.

Users can try out new versions of prior derivatives that only they can see, then they can test the new version, or compare the new version to the old version over time without impacting other users.

If managers and governance approve a new version, Liquify can facilitate the gradual or immediate transition from old version to new, depending on the need.

All users will have access to Ivy the Intelliguide at all times. Ivy is Liquify AnalyticsLab’s friendly interactive guide.  

Ivy’s technical foundation will be a sophisticated decision tree that is full of domain-specific knowledge coupled with at least 2 LLM integrations.  

Ivy will always know the user’s functional roles and abilities, basic persona, and full history of interaction with the Liquify systems. Ivy gets to know users, and can quickly tailor the product experience for each individual.

All your data is organized around business subjects you care about most, like customers, patients, accounts, and more.

Business users in the AnalyticsLab™ will use proprietary, subject-specific virtual ultra-wide views called WholeSubject™ Panoramas, along with coaching from the Ivy the Intelliguide, to gain access to every data point for their key subjects. 

Ivy the Intelliguide helps users find the data points they’re interested in based on the insights they want to gain from their data.

The WholeSubject™ Panorama is more than just a place to explore data or find information associated with your most important subjects – it’s a place where anyone can create any dataset they desire in an AI-coached, self-service way.  

Users are empowered to transform data, create all sorts of custom fields, and mature integrated datasets step-by-step.

Derived expressions or new data points from the operational systems that are added to the Reservoir immediately appear on the appropriate WholeSubject™ Panoramas in the AnalyticsLab™, making it possible to immediately use these data points for analytics.

Liquify innovates by knowing the recipes for all expression types, from simple, such as relabeling an existing field, to sophisticated and complex, where many fields from many different systems must be used in a formula to create a new value or measurement.  

Ivy the Intelliguide plays a critical role in coaching users through the self-service process of expression building too, enabling them to build expressions that satisfy their analytics requirements.

Just as datasets can be shared across workgroups, business units or the whole enterprise, custom fields can also be shared so they can be used again and again without having to be recreated. Before an expression can be published, it must be annotated so that everyone can understand how it was created and how it should be used.  

Governance and other approvers may scrutinize methods and formulas or provide technical collaborators to help users to improve them as needed.

Liquify will be released with hundreds of standard calendar-related reference data points that will be a part of every customer’s Reservoir. These data sets include Time Labels (Wednesday, January), Standard Periods (week, month, year), and Relative Sequencers (periods that are relative to today or a designated moment or period of time, such as “last quarter”).

Administrators and Managers can approve the sharing of custom calendars, custom periods and time-related labels and sequencers.  These can be company-specific or relate to important dates or periods in history (such as, “during the height of the COVID-19 pandemic”).

In the TimeSpanner, users can create custom periods and time-related labels and sequences as needed, with Ivy the Intelliguide to help them determine the right time boundaries for their business case.  

Custom time periods can be applied to any expressions or datasets. Can you imagine a data platform where it was possible to add new periods and timeframes to existing data without code? If you can, you’re imagining Liquify!

Once a dataset has been created, it can simply be used by its creator on an unlimited basis.  

Users can also ask for approval to share a dataset with their workgroup (a few people), business unit (several people), or company-wide. 

Users can request that governance approve the publication of their datasets. Publication allows other Liquify users or even external consumers, to access the dataset via an API or download it for a governance-approved time period. 

Once a dataset is published, analytics users such as analysts or data scientists can further enrich and present the data using the data science or BI tools of their choice.