What Is Data Fabric | How Data Fabric Works | Data Fabric Explained | Intellipaat

Summary

This Intel session introduces Data Fabric, a unified architecture that simplifies data management across various sources, enhancing digital transformation. It covers the concept, capabilities, and importance of Data Fabric, emphasizing its role in real-time data access, governance, and security. The session also explores its benefits for machine learning, customer insights, and multi-cloud environments, highlighting its potential to increase ROI and improve data-driven decision-making.

Takeaways

• 📈 Data Fabric is recognized by Gartner as one of the top 10 data and analytics technology trends for 2022.
• 🌐 A data fabric is a unified architecture that simplifies data management across various technologies and services.
• 🛠 Its primary goal is to maximize data value and accelerate digital transformation by providing real-time access to the right data with end-to-end governance.
• 🔄 Data Fabric supports end-to-end data management processes including integration, discovery, governance, curation, and orchestration.
• 🔐 Security is a critical component of data fabric, with measures like data encryption and private networking to protect against cyber threats.
• 💡 Data Fabric promotes a multi-cloud environment, allowing for flexibility and scalability in data management across different cloud platforms.
• 📊 It enhances machine learning model capabilities by streamlining data preparation and integration, leading to more efficient usage of ML models.
• 👥 Businesses can use data fabric to create a holistic customer perspective by integrating data from various customer touchpoints.
• 🚀 Data Fabric enables better utilization of existing data infrastructures without the need for complete application or data storage rewrites.
• 📊 The projected total economic impact of unified data fabric architecture includes increased ROI and faster data delivery, as shown in Forrester's 2020 study.

Q & A

What is a data fabric according to the Intel session?

A data fabric is a single environment with a unified architecture and services or technologies that help organizations manage their data, aiming to maximize the value of data and accelerate digital transformation.

Why is data fabric identified as a top technology trend by Gartner?

Data fabric is identified as a top technology trend because it provides a unified approach to managing and accessing data across different platforms and services, which is crucial for modern data-driven organizations.

How does a data fabric architecture facilitate data access and management?

A data fabric architecture simplifies data access and management by housing technology and services that aid in data management, making it easier for data-centric tools and applications to interact with various services and data sources.

What are the capabilities and principles of data fabric discussed in the session?

The capabilities and principles of data fabric include data integration, data discovery, data governance, data curation, and data orchestration, all aimed at uniting varied and distributed data assets for efficient management.

How does data fabric support real-time access to data?

Data fabric supports real-time access to data by providing end-to-end governance and allowing organizations to access the right data at the right time, at a reasonable cost.

What are some of the end-to-end data management procedures that data fabric can combine?

Data fabric can combine end-to-end data management procedures such as data integration, data discovery, data governance, data curation, and data orchestration to streamline data management across the organization.

Why is security a critical factor in data fabric implementations?

Security is a critical factor in data fabric implementations because it safeguards data at all stages, protecting against cyber attacks and ensuring the confidentiality, integrity, and availability of data assets.

How does data fabric promote a multi-cloud environment?

Data fabric promotes a multi-cloud environment by enabling organizations to manage and access data across different cloud platforms seamlessly, providing flexibility and scalability in data management.

What are some business use cases of data fabric mentioned in the session?

Some business use cases of data fabric include improving machine learning models by providing timely data, creating a holistic customer perspective by integrating data from various customer interactions, and enhancing data-driven decision-making.

What benefits does data fabric provide in terms of performance and data investments?

Data fabric provides benefits such as increased returns on investment, accelerated data delivery, improved customer affinity analysis, and optimized data investments by enabling high-performance data management and addressing technical constraints in multi-cloud and hybrid environments.

How does data fabric help in handling the scalability and complexity concerns of organizations?

Data fabric helps in handling scalability and complexity concerns by allowing organizations to manage existing applications and modern microservice-based applications in various contexts without the need to rewrite applications or data storage from scratch.

Outlines

00:00

📈 Introduction to Data Fabric by Intel

The video script introduces a session on Data Fabric by Intel, emphasizing the importance of subscribing for updates. It mentions that Gartner has identified Data Fabric as one of the top 10 data and analytics technology trends for 2022. Data Fabric is described as a unified architecture that simplifies data management across various technologies and services, aiming to maximize data value and accelerate digital transformation. The session agenda includes discussions on what Data Fabric is, its capabilities, why it's needed, business use cases, security, multi-cloud environment promotion, and its benefits.

05:01

🔍 Deep Dive into Data Fabric Capabilities and Principles

This section delves into the workings and capabilities of Data Fabric. It explains that Data Fabric is an architecture housing technologies and services for data management, making it easier for data-centric tools to access data through various interfaces like ODBC, HDFS, REST APIs, etc. It also highlights the need for Data Fabric to accommodate evolving standards and be agnostic to geographical locations, data use cases, processes, and deployment platforms. The paragraph outlines the end-to-end data management procedures that Data Fabric can integrate, such as data integration, discovery, governance, curation, and orchestration. It also discusses the various data management capabilities that Data Fabric can encompass, including semantics, access to global data assets, advanced AI for data relationships, and centralized data governance and security processes.

10:01

🛡️ Security and Multi-Cloud Benefits of Data Fabric

The final paragraph discusses the importance of security in Data Fabric implementations, given the high stakes of cyber attacks. It mentions various security measures such as data encryption, use of private links on cloud platforms, and safeguarding secrets and keys. The paragraph also highlights the value proposition of Data Fabric in multi-cloud environments, emphasizing its role in managing dynamic data demands across globally distributed infrastructure. It outlines the benefits of Data Fabric in providing a real hybrid cloud experience, seamless transitions to the cloud, faster insights, high performance, and optimized data investments. The paragraph concludes with a reference to a Forrester study that projects significant business benefits from implementing Data Fabric, including increased ROI and accelerated data delivery.

Keywords

💡Data Fabric

A data fabric is an architecture that integrates various data management tools, technologies, and services to facilitate unified data access across different environments. In the video, it is described as enabling organizations to manage and optimize data, regardless of where it is stored or how it is processed, to support digital transformation.

💡Data Integration

Data integration refers to the process of combining data from various sources into a unified view for users. The video emphasizes its importance in the context of data fabric, as it allows organizations to consolidate dispersed data assets, improving accessibility and usability.

💡Data Governance

Data governance is the framework for managing data quality, privacy, security, and compliance. In the video, it is highlighted as a crucial principle of data fabric, ensuring that data is managed responsibly at both macro and micro levels to align with global standards.

💡Data Orchestration

Data orchestration automates the processes of managing and preparing data from multiple sources for analysis. In the context of data fabric, it helps streamline complex workflows by unifying access, management, and control over distributed data assets.

💡Multi-Cloud Environment

A multi-cloud environment refers to the use of multiple cloud computing platforms to store, manage, and process data. The video explains how data fabric supports a multi-cloud setup by enabling seamless data management across various cloud providers, ensuring flexibility and resilience.

💡Machine Learning (ML) Models

Machine learning models refer to algorithms that learn from data to make predictions or decisions. In the video, data fabric is shown to enhance machine learning by optimizing data preparation and enabling timely access to relevant data, thereby improving the efficiency of ML models.

💡End-to-End Data Management

End-to-end data management covers the complete lifecycle of data, from collection to processing, storage, and analysis. The video discusses how data fabric unifies this lifecycle, ensuring that data is seamlessly managed across all stages to meet organizational needs.

💡Data Curation

Data curation involves organizing, annotating, and maintaining data to preserve its value and ensure long-term accessibility. In the video, data fabric is portrayed as aiding in data curation by integrating data from multiple sources and making it available for future use.

💡Real-Time Data Access

Real-time data access refers to the ability to retrieve and process data instantly as it is generated. The video highlights this as a key goal of data fabric, enabling organizations to make faster and more informed decisions by accessing the right data at the right time.

💡Data Security

Data security involves protecting data from unauthorized access, breaches, and loss. The video emphasizes the critical importance of security in data fabric deployments, outlining methods like data encryption and private cloud connections to ensure that data remains protected across all stages and environments.

Highlights

Data Fabric is identified as one of the top 10 data and analytics technology trends for 2022 by Gartner.

A Data Fabric is a unified architecture and services environment that helps organizations manage their data and accelerate digital transformation.

Data Fabric simplifies access to varied and distributed data assets by integrating tools and services across multiple platforms.

The architecture supports diverse data formats, including relational databases, tagged files, flat files, and graph databases.

Data Fabric allows real-time access to the right data with end-to-end governance at a reasonable cost.

Core capabilities include data integration, discovery, governance, curation, and orchestration, all unified under one architecture.

Data Fabric incorporates advanced AI systems for connecting relationships between data from various applications.

It provides centralized and standardized governance and security processes, using AI for policy application and compliance monitoring.

Data Fabric enables intelligent integration across distributed data and infrastructure environments, with future-proof, platform-agnostic design.

Security is a critical aspect, focusing on encryption during data transit and rest, along with secure cloud networking.

Data Fabric promotes a true hybrid cloud experience, allowing seamless transitions between on-premises, cloud, and multi-cloud environments.

Business use cases include improving machine learning models by reducing data preparation time and providing timely data to learning systems.

It helps create a holistic customer perspective by aggregating real-time data from sales operations and customer interactions.

Data Fabric optimizes data investments by ensuring high performance and scalability across different data storage and infrastructure solutions.

The architecture leads to a 459% increase in return on investment, along with significant improvements in data delivery and customer analysis.

Transcripts

hello everyone and welcome to this

session on what is data fabric by intel

apart

but before we begin with the session

please subscribe to our channel and hit

the bell icon for more updates from us

did you know according to gartner data

fabric is identified as one of the top

10 data and analytics technology trends

for 2022. in simplest terms a data

fabric is a single environment

consisting of a unified architecture

and services or technologies running on

that architecture

that helps organizations manage their

data the ultimate goal of data fabric is

to maximize the value of your data and

accelerate digital transformation in

this session you will learn all about

data fabric

so without further ado let's begin with

the session

let's

see what our agenda is

first we will discuss what is a data

fabric and how does it work then we will

discuss its capabilities and the

principles involved moving on we will

see why is it needed further on we will

discuss some of the business use cases

then we will discuss how security is the

most important factor

then we will see

how data fabric promotes multi-cloud

environment finally we will discuss its

benefits now let's see what is a data

fabric and how does it work a data

fabric is an architecture

that houses technology and services that

aid in data management relational

databases tagged files flat files graph

database bases and document stores can

all be used to store this information a

data fabric architecture makes it easier

for data centric tools and applications

to access data while interacting with

different services

odbc

hdfs

rest apis o6 nfs

and others are examples of these a data

fabric architecture must also be able to

accommodate an evolving standards the

architectural approach geographical

locations

data use case data process and

deployment platforms are irrelevant to a

data fabric

organizations can use data fabric to

strive toward

one of the most cherished goals

that is having real-time access to the

right data with end-to-end governance at

a reasonable cost

now let's take a look at the

capabilities and principles traditional

data management ideas like data ops

focus on the operationalization of

massive and scattered data assets

whereas the data fabric focuses on the

capabilities and

unite

varied and distributed data assets to

put it another way

most organizations use data ops

frameworks to design develop and

maintain a distributed data architecture

it aids in the interpretation of data

created and preserved in a highly

dispersed architecture the end-to-end

data management procedures are combined

when a unified data management platform

architecture such as data fabric is

introduced some of the end-to-end data

management procedures are

data integration data integration is

bringing together data from several

sources and giving people a single view

on it next we have data discovery it is

a process of gathering and analyzing

data from diverse sources in order to

identify trends and patterns in the data

next we'll talk about data governance it

is a phrase that can be applied

at both the macro and micro levels the

first is a political notion that is

related to

international relations and internet

governance while the second is a data

management concept that is related to

corporate data governance next we have

data curation the organizing and

integration of data acquired from

multiple sources is known as data

curation it entails annotating

publishing and presenting data in such a

way that the data's value is preserved

throughout time and the data is

available for reuse and preservation

lastly we'll talk about data

orchestration data orchestration it

automates data management operations

such as bringing data from many sources

together integrating it and preparing it

for analysis it can also encompass

duties such as resource provisioning and

monitoring all tasks are

managed through a unified platform

architecture that makes accessing

managing and controlling distributed

data assets easier a data fabric can

incorporate a variety of data management

capabilities in the logical domains

some of them are

semantics knowledge and insights users

can discover and retrieve relevant data

well thanks to semantic layers of

descriptions in the form of a

marketplace

access to a worldwide pool of data

assets analytical monitoring of ever

increasing data sets

advanced ai systems are being used to

connect business relationships between

data from many applications end-to-end

data management visibility allows you to

access numerous data properties and

risks next we have compliance and

governance in one place metadata

management on a local level in

accordance with global

organizational principles that apply to

all data sets automation and ai

capabilities complement data tracing and

root querying making it easier to apply

policies and check compliance as well as

discover potential system breaches

across all environments the whole data

governance and security process is

centralized and standardized as well

next we have intelligent integration

across distributed data and

infrastructure environments the design

deployment and use

are all integrated for sealer

data environments automated flow and

pipeline construction is available

schema drift correction and optimal task

distribution ingestion of new data

assets by self-service within preset

policies infrastructure that is future

proof platform and application

agnostic lastly we have orchestration

and life cycle management self-service

orchestration of diverse data sources

with advanced ai systems data lakes and

other platforms and technologies that

provide a holistic view of the data

pipeline across all data environments

data-driven applications use a unified

data life cycle to configure and manage

all parts of the data including

development operations testing and

production release

now let's see in today's digital

environment why do you need a

data fabric well data fabrics enable

enterprises to make better use of the

existing data infrastructures without

having to rewrite every application or

data storage from the ground up but why

is a data fabric important in today's

world organizations are dealing with

scalability and complexity concerns

their id systems are now advanced

just a quick info guys if you want to

make a career in cloud computing then

intellipaat provides advanced

certification in cloud and devops it is

taught by iit professors and industry

experts with more than 10 years of

experience this course is designed to

upskill and land your dream job now

let's continue with the session

allowing them to manage existing

applications as well as modern

microservice

based applications in a variety of

contexts adida fabric

aids

in the following shown tasks multiple

settings including on-premises

cloud and hybrid can be managed at the

same time to connect to any data source

you can use pre-packaged modules

strengthen your data preparation data

quality and data governance skills

improve data integration between sources

and applications now let's discuss some

of the business use cases of data fabric

first up we have improving machine

learning that is ml models our data

fabrics architecture flexibility is

beneficial in a variety of ways

let's discuss some of the instances

machine learning models increase the

learning capacities and the proper data

is provided to them in a timely manner

data pipelines can be monitored using

machine learning algorithms which can

also be used to identify appropriate

linkages and integrations getting the

data ready is one of the most time

consuming aspects of training ml models

by lowering data preparation time a data

fabric design aids in the more efficient

usage of machine learning models next

business use case we have is creating a

holistic customer perspective

businesses can use a data fabric to

collect data from client interactions

and figure out how to provide additional

value to customers

this might involve combining real-time

data from various sales operations the

time it takes to onboard a customer and

kpis related to customer happiness

now let's take a look at the next agenda

that is security a good data fabric

installation requires a very high level

of security with so many cyber attacks

resulting in millions of dollars in

losses

safeguarding your data at all stages is

critical to deploying your data fabric

design properly this can be dealt with

in a variety of ways encrypting data

while it is in its transit and at rest

using private link on azure and aws to

protect

your networking traffic from the public

internet keeping secrets and keys safe

in the cloud multi-cloud environment the

value proposition

that the data fabric gives

in id environments with dynamic data

demands distributed across globally

distributed infrastructure systems

data fabric architecture is very useful

in today's cloud-based enterprise i.t

environment the data fabric architecture

provides

the following benefits

a real hybrid cloud experience is made

available

organizations can use data fabric to

address the technical constraints of

managing a

broad portfolio of data

of data storage and infrastructure

deployments customers can choose from a

variety of hybrid id infrastructure

resources to run mission-critical

data-driven i.t services apps storage

and access based on change in technical

and business requirements then we have

seamless transitions to the cloud to

handle data stored in several places

data fabric is designed to minimize

disruptions caused by switching between

the cloud suppliers and computational

resources

as a result

data fabric drastically decreases the

time it takes to get insights

organizations can do the following with

faster insights

that is recognize patterns in data

make proactive decisions etc businesses

may outspace market competitors by

improving compute performance across all

data channels allowing them to make the

most of their data investments high

performance and data investments that

are optimized organizations devote

tremendous resources and efforts to

ensuring that their apps and services

work optimally this is specially true

for mission critical programs that may

be expected to process an increasingly

amount of data as the user base develops

or to handle unpredictable peak usage

demands

organizations must also invest in cloud

storage solutions

that offer the appropriate performance

levels in order to meet these needs

similarly the software or service could

become a legacy solution in the future

lowering the utilization need

in any case the app should be able to

give predictable results regardless of

whether the data is available at a solid

site with a lot of space

infrastructure for low cost economy

storage

organizations may take advantage of this

feature and optimize their data

investments based on changing app usage

requirements using data fabric now let's

take a look at the benefits the

following commercial value of

capabilities that make up unified data

fabric architecture

is shown

in the forester new technology projected

total economic impact 2020 study we have

459 increase in returns of investment

5.8 million dollars

business benefits on average

60 times accelerated data delivery 20

times faster customer affinity analysis

by tackling the technical constraints of

managing data services and a multi-cloud

and hybrid id environment

data fabric provides enterprises with a

variety of business value and

proposition that's it for this video

thank you

just a quick info guys if you want to

make a career in cloud computing then

intellipaat provides advanced

certification in cloud and devops it is

taught by iit professors and industry

experts with more than 10 years of

experience this course is designed to

upskill and land your dream job

you