vista

Kivyo Vista

Your Journey Towards Real-Time ML Starts Now

Vista’s Feature Platform for Machine Learning (ML) deployed on top of Snowflake Data Cloud enables organizations to securely and reliably build, store, and serve production-grade features across the enterprise.

Solution Overview

Together, Kivyo and Snowflake provide a simple and fast path to building and serving production-grade features that support a broad range of machine learning applications, including fraud detection, recommendation systems, real-time pricing, and much more.

Available to all Snowflake customers, Vista acts as the central hub for ML features, allowing data teams to define features as code using Python and SQL and then automating production-grade ML data pipelines to generate accurate training datasets and serve up-to-date features online for real-time inference

About Vista

Made Easy with Vista

Vista is a feature platform for real-time machine learning (ML). The platform is fully managed and helps data teams accelerate the iteration and deployment of real-time ML models while maximizing their accuracy and reliability. Vista simplifies feature management and optimizes the cost of running models, enabling data teams to avoid expensive infrastructure costs. Vista’s platform streamlines workflows and allows teams to focus on developing better ML models, resulting in improved business outcomes. Vista’s customers include Fortune 500 companies and innovative firms like Verizon, Workday, Vertex, and Rackspace

How It works

Sitting on top of the Snowflake Data Cloud and its powerful processing engine for Python and SQL, Vesta feature platform enables data engineers and data scientists to build production-ready feature pipelines, and serve them at scale across teams, systems, and models, with only a few lines of code. Under the hood, Vista abstracts and automates the complex process that transforms raw data from batch, streaming, or real-time sources into features used to train ML models and feed predictive applications in production. Managing the ML feature lifecycle with Vista not only ensures that feature materializations are always consistent, online for training, and offline for inference, but that they are also stored in a searchable repository for easy sharing and re-use across teams and use cases.

Key Challenges of Production ML

Whether you’re building batch pipelines or already including realtime features in your ML initiatives, Vista solves the many data and engineering hurdles that keep development time painfully high and, in many cases, predictive applications from ever reaching production at all, including:

Training-serving skew
Point-in-time correctness
Productionizing notebooks
Real-time transformations

Melding batch + real-time data
Latency constraints
Data scientist and data engineering siloed workflows
Limited discovery and re-use of features across teams

Key Benefits

Power

Build more powerful models by easily incorporating batch, streaming, and real-time data.

Speed

Deliver value from real-time models in minutes rather than months.

Flexibility

Continuously improve and iterate on production MLmodels across teams and use cases.

Data Governance

Manage your own automated hub for external data datasets, enabling teams to focus on more value-added tasks.

Vista’s platform puts our robust integration capabilities directly in your hands, and increases the velocity of data teams.

An automated hub for your external data

Use Vista to make managing external data sources easy, automatic, and scalable

Connect to your licensed or public external data sources via FTP, SFTP, GCS, or S3
Decide when data is delivered according to your schedule
Deliver to BigQuery, Snowflake, GCS, S3, FTP, and SFTP

A faster way to data operations maturity

Skip data org growing pains – get data that is normalized automatically

Automatically profile data to detect delivery patterns
Manage changes and map multiple schemas
Backfill data from any date range available from your data supplier
Receive data delimited in the format you prefer

A source of truth and data reliability

Vista comes with governance and observability tools built in

Monitor the status of all active data pipelines in the APP data health dashboard
Receive alerts and triage info for data quality and availability issues
Role-based access controls available to fit your teams needs

The Vista Platform was built for data teams with an insatiable appetite for external data

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Active Aata Pipelines

World-Class Teams Choose Kivyo and Snowflake

The complete SaaS ELT platform for Snowflake

Kivyo addresses the entire journey of loading, transforming, and activating your data with Snowflake, by providing a unified, SaaS solution for both technical and non-technical users. With Snowflake & Kivyo, you can focus on your business, not on managing your data & pipelines.

A complete data solution

Kivyo provides all of your integration needs in a single solution: Extraction, Transformation (ELT), Change Data Capture, Data Activation / Reverse ETL, and Data Operations. Everything works together in harmony, giving you fast integrations and easy insights.

That's easy to use & maintain

Get started in minutes with Snowflake Partner Connect, and easily build advanced & reliable data pipelines without code. Snowflake integrations-made- easy with 200+ fully-managed connectors & no-code custom connectors. Instantly install complete Snowflake data solutions with our Starter Kits.

And powerful enough to handle complex data needs

Snowpark & native Python support for infinite extendibility. Advanced workflow orchestration & scheduling. Developer friendly with multiple environments, Cl/CD support, and version control. Integration friendly & easily extensible with our robust API and CLI tools.

We know Snowflake

Why Kivyo for Snowflake?

200+ fully managed connectors

Get data from any source, avoid updating APIs, and connect to every system.

Support for CDC & SQL based replication

Migrate your database to the cloud, efficiently and without disruption.

Low-code interface

Accelerate onboarding, create pipelines in minutes, and become data driven.

Custom file zones

Take control of your data storage and enhance security and privacy.

Capabilities

Snowflake-ready technology validation partner

20+

Active Snowflake engagements

50+ Team

of Snowflake experts with 30+ Snow Pro certifications

9.2 /10

CSAT score 50+ team

Focus Areas

Snowflake migration expertise including Oracle, Hadoop, Teradata, and SQL

Presence in Snowflake ecosystem eg., AWS, Azure, StreamSets, Matillion, PkWare,Colibra, Alation

Multiple use cases and domains, eg.,marketing, revenue, commerce, patient 360, and genome sequencing

Variety of Snowflake workloads managed including data platform, data mesh, and cloud warehouse

Vista & Snowflake

How Vista Helped Kivyo Save 25% Per Month in Snowflake Costs

About DTCC Media DTCC Media is a leading media company in Europe, known for its diverse portfolio of news outlets, radio stations, magazines, and digital platforms. The company serves 15 million viewers, readers, surfers and listeners in Belgium,the Netherlands, and Denmark.

DTCC Media was facing increasing Snowflake costs and redundancies across multiple business domains. They needed an efficient data solution that aligned with Data Mesh principles, promoting data ownership and facilitating central governance standards through automation.

Managing Snowflake Costs at DTCC

Vista provided Kivyo with a detailed overview of their data usage, helping them identify areas of inefficiency and reduce waste.

Step 1 - Setup and Integration

The customer first integrated Vista’s platform with their Snowflake data warehouse and Looker dashboards and charts. This allowed Acryl to analyze DTCC Media’s data usage, lineage and other signals to estimate Snowflake costs.

Step 2 - Implementation of Metadata Tests

The customer utilized Vista’s Metadata Tests to monitor their data usage continuously and flag datasets that had low usage but had high costs (determined through proxy cost signals like storage footprint)

Step 3 - Elimination of Redundant Data

DTCC Media was able to use the results of Metadata Tests in conjunction with Lineage and Impact Analysis features to confidently retire datasets rapidly with no disruption to the business.

Step 4 - Continuous Monitoring and Optimization

Metadata Tests are built for continuous monitoring of rules on top of Vista’s metadata graph. By implementing these tests, DTCC ensures that data cleanup efforts are not limited to a one-time occurrence. Instead, future inefficiencies will be proactively identified and addressed
to prevent cost overruns.

Vista provides DTCC Media with central governance on top of a decentralized data mesh. By leveraging Vista’s Metadata Tests, they saved 25% per month in Snowflake costs, and also gained valuable insights into their data usage to further ensure the success of their data mesh strategy.

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