White paper

VantageCloud Lake
Product Overview and Customer Benefits
Robin Jessani
Technical Product Marketing

Version 2.0

Table of Contents

3

Overcoming challenges witha cloud-native design
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3
4
4
4

5

An architecture built
for superior performance

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9

Restrictive policies
Disjointed tools and services
Resource contention
Isolated data silos
Suboptimal governance

Point of deployment (POD)
ConsolePrimary cluster
Compute clusters
Lake File System (LFS)
Query fabricInnovate faster, scale smarter,
govern better
Empowering faster innovation

9 Advanced analytics
10 Open and connected ecosystem
10 Business autonomy

11 Enabling smarter scaling
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11
11

Growth optimization
Flexibility and sustainability
Scalability

12 Supporting better governance
12 Cost visibility
12 Centralized management
13 Lower total cost of ownership

14 Summary2Overcoming challenges
with a cloud-native design
In recent years, the rapid growth of cloud technology has
transformed the data and analytics landscape in profoundways. With cloud adoption becoming widespread, Teradata
seized on this opportunity with the development of an
offering that capitalizes on cloud-enabled frameworks
to extend the capabilities of VantageCloud, Teradata’s
complete analytics and data platform for trusted AI.
This innovative deployment option, VantageCloud Lake,is built on a next-generation, cloud-native architecture,enabling businesses to meet the full spectrum of analytic
enterprise workloads, including AI/ML, in the cloud. With its
cloud-native design, VantageCloud Lake delivers advanced
analytics to users of any skill level while also overcoming
the main challenges that customers contend with in their
existing data analytic ecosystems. These include:• Restrictive policies• Disjointed tools and services• Resource contention• Isolated data silos• Suboptimal governance
Together, these factors can create significant obstacles
that slow innovation and impede business growth. Below
we’ll examine each of these challenges and explore how
VantageCloud Lake addresses them to help companies
fast-track digital transformation and drive breakthroughbusiness outcomes.

VantageCloud Lake helps companies
fast-track digital transformation anddrive breathrough business outcomes

Restrictive policies

To protect SLAs, many companies adopt restrictive policies
that require heavy reliance on IT for operational support,
inadvertently introducing extra steps and bottlenecks thathinder innovation. But as the use of public clouds grows,
stakeholders are increasingly demanding technologies
that deliver greater autonomy and agility. Customers today
require self-service independence that applies to all lines ofthe business, including Finance and Marketing.
VantageCloud Lake addresses this expectation byoffering a self-service environment that enables businessdepartments, teams, and users to provision, manage, andoperationalize their own dedicated resources with little
to no administrative involvement. Providing this level ofunrestricted independence gives users the agility they needto quickly react to volatile business goals and accelerateinnovation for the company.

Disjointed tools and services

As cloud computing adoption increases, so does software
specialization. Many cloud service providers (CSPs) andthird-party software companies offer an extensive suiteof analytics tools and services that are attractive or evenrequired for the business. Key stakeholders, like developers
and data scientists, need access to these industryleading technologies so they can innovate efficiently andeffectively. While external tools and services can offer an
intelligent way to enhance platform functionality, they cancreate management inefficiencies if they’re not connectedto the underlying platform.
VantageCloud Lake addresses this concern with an open
and connected environment, leveraging open APIs tointegrate with and manage a wide range of third-party tools
and services on one platform. This significantly improves
management efficiencies while enabling users to use theirpreferred tools and services, accelerating time to value.

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Overcoming challenges with a cloud-native design

Resource contention

There are often conflicting priorities when resources are
distributed across the organization, and workloads withstrict mission-critical SLAs risk jeopardy or disruption fromgrowing demands. System workloads have to contend
for shared resources, requiring IT to manually prioritize
and allocate them based on workload importance. And
when storage and compute resources are finite andcoupled together, this negatively impacts business-critical
workloads due to growing demands between teams. Ad hoc
and exploratory workloads slow down performance, andcomplex analytics queries risk disrupting critical workloads.
Lines of business need their own independent compute sothey can isolate their workloads from one anotherand accelerate innovation without this risk. VantageCloud
Lake enables this by leveraging the cloud to separate
compute and storage resources so that departments
can have isolated and scalable multi-cluster compute.
This eliminates resource contention by giving teams theflexibility to provision and regulate their own computeresources while not impacting workloads outside of theirteam or department.

Suboptimal governance

Suboptimal governance and spend management practices
make it challenging for businesses to effectively oversee
their investments and finances. In the absence of
sophisticated cloud technologies, organizations rely on
manual governance processes, leading to errors and missed
opportunities. As a result, they tend to overspend on theirinvestments, underutilize their resources, and overlook
optimization opportunities.
VantageCloud Lake solves for this by providing an
extensive range of governance capabilities for bothadministrators and analysts, enabling customers to makethe most of their investments. Administrators can utilize
graphical resource consumption telemetry and query
monitoring insights to make informed, agile decisions
for the organization’s performance tuning, forecasting,and budgeting. Analysts can utilize VantageCloud Lake’s
differentiated auto-scaling algorithm and policy-driven
guardrails, such as the max number of auto-scalable nodes
and on/off scheduling, to optimize resource usage. All ofthese governance capabilities work together to increasecustomer ROI while reducing total cost of ownership.

Isolated data silos

Data movement costs the business time, manpower, andmoney. Many customers have spent millions of dollars
moving their data into isolated pipelines and silos over
the years, creating massive tech debt and management
problems. These data silos are often created for short-term
projects, only to end up underutilized or even forgotten—all
the while incurring ongoing costs. Businesses need a way toconsolidate and share their data against a single data store.
VantageCloud Lake addresses this issue by integratingwith low-cost, third-party object storage to ingest andconsolidate all sources of data. It also provides support for
open table formats (OTFs) and open file formats, enablingusers to effectively manage and query data within theobject store. Data living in the object store can be accessed,
shared, and queried across the ecosystem of connected
systems. VantageCloud Lake’s harmonized data approachsignificantly reduces data movement while minimizing costs
accrued from poorly managed or forgotten data pipelines.
The object store introduces additional cost savings by
operating independently from compute. This separation ofstorage from compute allows customers to elastically growor shrink their storage capacity without impacting their
compute resources, providing them with the flexibility toefficiently manage each resource as required, ultimately
optimizing resource allocation and reducing overall costs.

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An architecture built
for superior performance
The introduction of VantageCloud Lake advances
Teradata as a leader in cloud analytics and data. With its
reengineered architecture and industry-leading Analytics
Database, VantageCloud Lake lends itself to modern
cloud capabilities to bring superior performance acrossall enterprise workloads at scale. Analytics workloads ofany requirement, whether business critical with tight SLAs,
transactional, AI/ML, data engineering, or data science,
can be executed to unlock profound discoveries that cantransform the business.
To better understand how the new architecture resolves
customer challenges, let’s take a closer look at thecomponents that comprise the VantageCloud Lake techstack: point of deployment, Console, primary cluster,compute cluster, Lake File System, and query fabric.

Point of deployment (POD)

Not depicted in the graphic below is the POD mechanismthat supports all activity taking place in the VantageCloud
Lake platform. Each POD can support one to many customer
accounts, known as tenants, which are separate databaseinstances. Because tenant environments are logicallyisolated from one another, the failure of a single tenant will
not affect others.

ConsoleThe VantageCloud Lake Console is the web-based firstpoint of entry for users. It’s an easy-to-use, self-service
browser with centralized navigation that contains anarsenal of capabilities that administrators and users willcommonly interact with. These capabilities are accessible
with single sign-on (SSO) login, providing both security andconvenience as users access their data and initiate sessions
to all connected applications.
Console functionality is enhanced with ask.ai, Teradata’s
generative AI-powered tool. In private preview, ask.ai is
a natural-language interface that enables users to “talk”
to the platform to explore, analyze, and make knowledge
and data intelligence decisions instead of using complex
tools and processing languages. This brings a new levelof accessibility to wide range of users, not just those withadvanced skill sets and knowledge of business intelligenceand data science tools.

5An architecture built for superior performance

The Console serves three personas, each with their own
pain points and requirements that the Console addresses:• Administrators: The Console serves administrators
by offering self-service provisioning, simplified user
management, and performance monitoring to help
identify and optimize slow-running queries. It provides
graphical telemetry of the organization’s compute andstorage consumption that can be drilled down to thedepartment level, and it includes filters for time, time
ranges, and contract terms. And with the integration of
ask.ai, administrators can retrieve system information
effortlessly through natural-language queries and accessto real-time support.
• Business analysts and citizen data scientists: The
Console’s self-service, user-friendly features enable users
to perform analytics effectively and easily identify key
insights. It offers various low-code/no-code data movement
tools that simplify data access and collaboration acrossthe organization to accelerate data exploration. The
Function Explorer facilitates direct access to ClearScape
Analytics™, Teradata’s advanced analytics capabilities
within VantageCloud Lake, by offering clear instructions forbuilding queries using the full catalog of in-database AI/ML
functions. This allows users to efficiently construct complex
queries like nPath analyses. When coupled with ask.ai,
the Console flattens the learning curve, enabling users togenerate data-driven insights without having to manuallyconstruct queries and scripts.
• Technical users: The Console empowers developers,
data engineers, data scientists, and other technicalusers by simplifying advanced analytics processes. The
Function Explorer offers a simplified user experience,
allowing users to easily find in-database analytic
functions that meet their needs. With ask.ai, users canmake requests like “Find and correct inconsistent fields
across this dataset” or “Identify and resolve the syntax
error in this line of code” to speed up data preparation
or model creation steps and enhance productivity.
The Console also integrates seamlessly with external
partner tools and services through an API-driven, open
ecosystem, enabling users to leverage their preferredtechnologies and streamline tasks such as model building
and deployment for advanced analytics.

Primary cluster

Each environment has a primary cluster that’s configuredin the Console during the provisioning process. Users caneither set up this pattern or leverage the primary cluster
as an independent database system. This is very powerful,as customers can migrate to the primary cluster and thenmodernize by leveraging the compute clusters selectively
by workload at their own pace.
There are several use cases that are uniquely addressedwith the primary cluster because it leverages persistent,
high-performant block storage associated with eachaccess module processor (AMP). Customer lift-and-shift
migrations to the primary cluster are the easiest, fastest,
and lowest-risk way to migrate to VantageCloud Lake,with gradual workload modernization leveraging compute
clusters and low-cost object storage occurring afterwards.
Additionally, the primary cluster is optimized for enterprisetransactional queries at scale, enabling strict missioncritical SLAs for workloads that require predictablesub-second performance.
The primary cluster architecture is the same as ananalytics database, consisting of interconnected nodes
with AMPs that handle data processing, movement, andmanagement from disk drives. This design allows theprimary cluster to efficiently distribute workloads across theuser environment for optimized query planning.

6An architecture built for superior performance

Compute clusters

Compute clusters operate on nodes independent fromthe primary cluster to serve unique functions. They arehighly elastic by design and can automatically scale on/off
and up/down in accordance with the user’s policy-driven
configuration, enabling the system to automatically optimize
compute resource allocations based on various parameterslike resource utilization and workload priority. Compute
clusters leverage object storage to store large volumes ofdata in a cost-effective manner, while the primary cluster
stores the required metadata. An environment can havezero to many compute clusters; it depends entirely on how
much compute is needed to complete the query queue
within the expected time frame.
Compute clusters are used to execute a broad range
of enterprise workloads, including analytics, reporting,
ELT, and departmental workloads. Teams like Finance orMarketing can dynamically provision multiple compute
clusters against a single data store and will have their query
work executed on their own dedicated resources.
Analytics compute clusters are also offered to support
memory-intensive analytic applications that rely on
in-database and/or imported analytic functions to run in
a containerized, open analytics framework. They provide
twice as much memory as standard compute clusters andtherefore are ideal for advanced AI/ML workloads like datapreparation and model building/training/operationalization.
Since compute clusters are independent of one anotherand rely on the primary cluster to send them work, they
can be added or removed as needed. More importantly,
the failure of a compute cluster will not disrupt work being
processed elsewhere.

Lake File System (LFS)The LFS is VantageCloud Lake’s unified data storage systemthat supports block storage via the Block File System (BFS)
and object storage via the Object File System (OFS). Whilecustomer-owned data stored in object storage can beaccessed outside of VantageCloud Lake using Teradata’s
Native Object Store (NOS), many attractive benefits are
gained by ingesting data into the LFS, such as accessto Teradata’s Analytics Database capabilities, optimized
performance, and data sharing between connected
Teradata systems. The BFS manages tables stored in blockstorage available only to the primary cluster. Block storage
uses AMP storage to offer persistence for business-critical
workloads that require high reliability and low latency fortactical workloads with strict SLAs.

The OFS manages tables stored in object storage
available to both compute clusters and the primary cluster.
Object storage is low cost and therefore a preferrable
solution for reducing storage costs tied to large volumesof data. It also takes advantage of the compute clusterarchitecture to scale and isolate workloads. From aworkload perspective, object storage is a preferrable
storage solution for analytics workloads that are not time
sensitive or are generally long running.
The combination of the OFS and compute clusters
enables complete separation of compute and storage: datastored within VantageCloud Lake is accessible to compute
clusters independently managed by different teams. Thisarchitecture makes the system fully scalable, with eachteam managing its own compute resources without needing
to move or copy shared data.
VantageCloud Lake further enhances data management
by supporting OTFs like Delta Lake and Iceberg. Integration
with OTFs enables data living in customer-owned
object stores to be centrally managed and optimized
for performance on one OTF storage layer that sits on
top of the object store. The OTF storage layer brings
fundamental database capabilities to customers’ data
lakes with interoperability across a broad range of open
file formats and storage types. This enables seamless datapreparation for any language or framework and significantly
reduces data management complexities and replication
across the VantageCloud ecosystem. Once the data has
been prepared, it can then be brought into the LFS to takeadvantage of ClearScape Analytics for high-performancequery execution.

Query fabric

Query fabric is powered by Teradata’s QueryGrid software,
allowing VantageCloud Lake systems to connect to datastores and processing engines between multiple systems
to enable a hybrid, multi-cloud ecosystem. Query fabricfacilitates data connectivity within the ecosystem while alsoenabling push-down processing to send query instructions
to the data at its source, creating a harmonized dataapproach that minimizes data movement. Query fabricalso significantly improves query performance throughthe strategic use of bidirectional connectors for workload
parallelization and Teradata’s Query Optimizer tool forplanning query paths across systems. This results in aseamless and high-performing query federation, bridging
the gap between both Teradata sources and external data
sources for comprehensive analytics while eliminating theconstraints of data silos.

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Innovate faster,scale smarter, govern better
The architectural components of VantageCloud Lakeenable customers to achieve three key goals:• Innovate faster: Customers can capture a greater ROI andachieve a faster time to value. VantageCloud Lake’s selfservice, user-friendly interface flattens the learning curveso that users of any skill level are empowered to drive
data-driven insights with agility. The environment is open
and connected to external technologies and includes
over one hundred in-database functions to speed up datapreparation and model operationalization workflows while
enhancing the ability to extract value from data.
• Scale smarter: VantageCloud Lake is an environmentally
sustainable and economical platform, optimizing resource
utilization to ensure customers only pay for the resources
they use. Teradata’s smart-scaling technology provides
dynamic resource allocation, delivering cost-effective andautomated scaling as business needs evolve.

• Govern better: VantageCloud Lake equips customers withcentralized management over the entire organization’s
financial governance. Through consumption telemetry
with visualizations and data filtering, administrators
gain tighter control. This enables streamlined resource
management, eliminates overruns, and empowers user
flexibility without disrupting core operations.
In the next section, we’ll examine the key drivers behindeach of these benefits.

VantageCloud Lake’s self-service,user-friendly interface flattens the learning
curve so that users of any skill level areempowered to drive data-driven insights
with agility

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Empowering faster innovation

Advanced analytics

ClearScape Analytics is a comprehensive suite of
powerful analytical capabilities seamlessly integrated into
VantageCloud Lake. This integration is a standout featureof VantageCloud Lake, setting it apart from other data
analytics platforms. ClearScape Analytics serves as anindustry-leading advanced analytics solution that addresses
every aspect of the analytics lifecycle to deliver accelerated
value at scale. From streamlining data preparation to
enabling efficient model deployment, ClearScape Analytics,
in conjunction with VantageCloud Lake, empowers
organizations to:• Accelerate data preparation time by up to 70%• Go from a few models to millions of models at oneseventh the cost
• Deploy models in minutes or days and operationalize
them at scale

ClearScape Analytics makes this possible with features like:• The most extensive, versatile in-database functions forbetter data prep, model training, and deployment to solve
complex analytic problems, minimize risk, and deliverinsights based on a complete view of your data—all withzero data movement• Frictionless connectivity to a variety of open-source andpartner AI/ML tools to make it easier to access insights
and maintain the flexibility to make the right choices
for your business, resulting in increased efficiency andreduced time to value• Integrated ModelOps, with capabilities including
standardized lifecycle management, automatedmonitoring, simplified deployment, and advanced
governance, which removes the friction of getting AI/ML
models into production and cuts deployment time frommonths to days
• Bring Your Own Model (BYOM) and Bring Your Own
Analytics (BYOA) capabilities that make it easy for data
science teams to operationalize externally developedmodels, accelerating time to value and delivering
improved growth and performance for all models, eventhose developed in other tools
Users of any skill level have direct access to ClearScape
Analytics via the ask.ai tool (in private preview). With ask.ai,
business analysts and citizen data scientists are empowered
to quickly explore data and generate analytics insights byasking questions in natural language as opposed to manuallyconstructing queries and scripts. For example, “What are
the sales numbers of my product in Colorado over the last
five years?” or “What were the top-selling products during
the week before Christmas in Colorado last year?” can beprompted in plain language and a response will be received
instantly. The richness of ClearScape Analytics’ in-databasefunctions, combined with the natural-language interfaceof ask.ai, flattens the learning curve for nontechnical users
and accelerates time to value for technical users so that theentire business workforce can innovate faster with their data.

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Empowering faster innovation

Open and connected ecosystem

By offering an API-driven, open, and connected ecosystem,
VantageCloud Lake’s analytic capabilities are extended
to a broader range of technologies. Customers gain acompetitive advantage by integrating their environment withexternal tools and services that boost efficiency and serve
unique use cases.
This interconnection with the public cloud infrastructure
extends to every facet of the data analytics journey. Data
stored in other Teradata systems or external locations iseasily accessed through NOS, fostering data consolidationand the elimination of data silos. Partner integrations
with modern data stack tools like dbt and Airbyte simplify
ELT and data preparation tasks. For analytics, users canaccess VantageCloud Lake through Jupyter Notebook
to write in Python or R languages and create detailed
visualized reports that effectively convey insights. They
can also leverage BYOM or Bring BYOA to optimize modelbuilding and deployment workflows, accelerating theoperationalization of advanced analytics. This level offlexibility allows customers to use cloud technologies thatbest align with their business needs.

Business autonomy

VantageCloud Lake provides businesses with greater
autonomy, empowering every facet of the organization todrive transformative innovation. Departments and teams areequipped with dedicated yet independent resources that
ensure workloads do not disrupt one another, thus enabling
workload isolation throughout the organization. Self-service
provisioning of scalable resources eliminates reliance on
IT and associated waiting times. Collaboration is fosteredthrough services like in-place data sharing that facilitate thesecure sharing of private data between teams.
Autonomy is further enhanced by Console features thatare self-service and easy to use. These features empowerusers of any skill level to independently perform analytics,
freeing the organization from technical barriers andbottlenecks that slow down innovation. VantageCloud Lake
offers a wide array of user-friendly data movement toolsthat streamline data accessibility and collaboration between
teams for accelerated data exploration efforts. The Function
Explorer and Query Builder tools provide clear, step-bystep instructions to aid users in easily crafting queries using
ClearScape Analytics’ extensive library of in-databasefunctions. If that isn’t enough, the generative AI-powered
ask.ai tool paves the way for a simplified analytics journeyfrom start to finish, fostering innovation at warp speed forusers of any skill level.

10Enabling smarter scaling

Growth optimization

Compute clusters are highly elastic and automatically scaleusing Teradata’s “scale smarter” algorithm, which allocates
additional compute resources only once existing resources
have been fully utilized. While other platforms may trigger anauto-scale after an ambiguous limit has been surpassed, suchas query volume or user concurrency, VantageCloud Lake
optimizes growth by making sure that a compute cluster is fully
used before auto-scaling another one, ensuring that customers
only pay for the resources they use. Policy-driven guardrails arealso included to offer tighter controls for optimizing investment
efficiency and staying within budget as teams expand andgrow. When combined with Teradata’s workload management
expertise and its Query Optimizer tool, which optimizes queryprioritization and resource distribution, customers know that
their fixed resources are being optimally utilized.

Teradata’s smart-scaling technology
provides dynamic resource allocation,delivering cost-effective and automatedscaling as business needs evolve

Flexibility and sustainability

VantageCloud Lake’s cloud-native architecture supports
multi-cluster auto-scaling. This capability enables eachdepartment, team, and individual to dynamically andautomatically grow and shrink their specific environment
without disrupting or impacting other environments,
creating a seamless coexistence between the organization’s
resources and operations. This empowers customers tostay agile in the market with flexible and sustainable scalingacross the entire organization.

Scalability

Teradata’s scope of scalability is proven to be industry leading.
With over 1,000 nodes successfully scaled and benchmarked,
without any outages or downtime, VantageCloud Lakedemonstrates that it can handle workloads of the largest andmost complex customer environments.

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Supporting better governance

Cost visibility

The VantageCloud Lake Console provides detailed
telemetry data of the environment to facilitate financialtransparency and chargeback to customers. Graphicaltelemetry of storage and compute consumption, which
can be drilled down to the department level, is provided
with time, time range, and contract term filters. This makes
it easier for administrators to navigate and comprehend
financial telemetry data, enabling greater agility andaccuracy in their decision-making. Additionally, the Console
includes cost avoidance metrics like cost-performance ratio
to help manage budgeting and unit allocation.
The generative AI-powered ask.ai tool also facilitatesadministration. Using natural language, administrators caneasily retrieve system information related to VantageCloud
Lake, such as the status of the environment and computegroups. With a question like, “Which compute groups areactive and what’s the consumption of each?” administrators
can identify compute groups that are active but not in use,presenting an opportunity to hibernate them and save costs.
Additionally, ask.ai has access to general documentation, so
users can get immediate assistance when they encounter
problems or have questions.

Centralized management

In conjunction with enhanced cost visibility, VantageCloud
Lake enables centralized management across theorganization. From a financial governance standpoint, thismeans that administrators have the power to centrally
access, manage, and bill each department for the resources
they use. Management capabilities also extend to queries
with Teradata’s Active Query Monitor, which provides asummary view of active and completed queries. Having
these capabilities on one centralized platform ensures
access to valuable, detailed insights on each limb of thebusiness, helping administrators to make informed, accurate
decisions and govern their investments better to meet theneeds of the business.

.

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Supporting better governance

Lower total cost of ownership

VantageCloud Lake offers several advantages that allow
customers to lower their total cost of ownership, including:• Separation of compute and storage: Computing andstorage resources are now separated, so users cangrow their compute without having to incur the costs ofgrowing their storage (and vice versa).
• Flexible compute clusters: Compute clusters can beprovisioned and deprovisioned based on fluctuating needs(ad hoc workloads, weekends, holidays, seasonal lulls, etc.).
This allows for increased financial control over when totactically grow or shrink compute resources in accordancewith project timelines and query complexity/priority.
• Flexible object storage: Massively scalable, low-coststorage options include the OFS, open file formats, andopen table formats. The OFS is a Teradata-managed, fully
ACID-compliant data lake, optimized for performance
including caching, spool, and index metadata. Open fileformats (Parquet, JSON, CSV) and open table formats(Iceberg, Delta Lake) enable shared access to customermanaged data lakes. This architecture provides customers
with flexibility to choose the most appropriate storage
solution based on workload requirements and budget.
• Self-service accessibility: Self-service accessibility
reduces IT overhead by reducing labor-intensive
administrative tasks, such as provisioning the system,
managing environments, and installing software.
• Reduced data duplication and movement: The LFS
enables organizational teams on the same system toshare one copy of the same data. QueryGrid enables
push-down processing that function-ships query
instructions to the data at its source. As a result, data
duplication and movement are significantly reduced,
decreasing any associated egress costs.
• Auto-scaling guardrails: Users can designate policydriven guardrails for each compute cluster to ensure thatcosts associated with auto-scaling meet expectations.
These guardrails include parameters such as maximum
number of auto-scalable nodes and on/off scheduling.
• Auto-scaling trigger: Instead of triggering a compute
cluster to auto-scale after an ambiguous limit has beensurpassed, Teradata offers an optimized algorithm that
ensures compute resources are fully utilized before
initiating the next batch of resources. This ensures that
customers only pay for the resources they use.

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Summary

In summary, VantageCloud Lake offers a transformative
solution that enables customers to innovate faster, scale
smarter, and govern better. Its robust architectural designand cloud-enabled capabilities empower users of any skill
level to execute all types of data analytics use cases acrossthe entire organization. The integration of the generative AI–
powered ask.ai tool further reinforces a new standard for data
analytics, propelling organizations into the future of datadriven success. VantageCloud Lake is available for purchaseat www.teradata.com.

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