Mais conteúdo relacionado Semelhante a Data Has A Shelf Life: Why You Should Be Thinking About Real-Time Analytics (20) Mais de Bernard Marr (20) Data Has A Shelf Life: Why You Should Be Thinking About Real-Time Analytics1. Data Has A Shelf Life:
Why You Should Be Thinking
About Real-Time Analytics
2. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Title
Text
Introduction
Introduction
Real-time analytics enable companies to see, understand, and work with data
as soon as it arrives, which helps companies make better business decisions and
create smarter products. Find out how your company can get ready to work
with data in real-time.
Data Has A Shelf Life: Why You Should Be
Thinking About Real-Time Analytics
3. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
We are now living in a world where real-time and streaming data analytics are
becoming increasingly important.
Most companies recognize that data has a shelf life, and the sooner they can
use the data and turn it into insight, the more profitable it will be for their
businesses.
4. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
The Biggest Benefits of Real-Time And Streaming Data
Equalum is a big data ingestion and integration platform which enables real-
time analytics, and I recently spoke with their, Co-Founder and CPO, Erez
Alsheich. He said:
“Analytics is about getting insights from your data – but the vast majority of
companies are using batch technologies to load data into their analytic
platforms. Every night, they pull a bunch of data all at once, then load it into
the analytical environment. The next day, the rest of their team can do
analytics on that data, but the problem is that the information is already
outdated. It’s yesterday’s data.”
5. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
The Biggest Benefits of Real-Time And Streaming Data
The volume and velocity of data are ever-increasing, causing strain on legacy architectures
as they attempt to process it both efficiently and effectively. The complications of
ingesting data from operational sources in near real-time, transformed and optimized, do
not come without complexity, but the true gateway to streaming analytics lies in modern,
multi-modal change data capture.
Change Data Capture (CDC) is a low overhead and low latency method of extracting data,
compared to traditional batch processes, limiting intrusion into the source and
continuously ingesting and replicating data by tracking changes to that data. When
designed and implemented effectively, CDC is the most efficient method to meet today’s
scalability, efficiency, real-time, and low overhead requirements. You can push changes as
they happen to your streaming analytics systems to enable faster and better business
decisions, create smarter products and services, design recommendation services for
customers and improve and automate business processes.
6. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
The Biggest Benefits of Real-Time And Streaming Data
While streaming real-time data is a vital component of any modern architecture, there will most likely
still be a place for batch data processing in the years to come. Monthly reports, data with minimal
changes, historical assessments, and more can still be processed using a batch approach and may not
need to be delivered in real-time. Additionally, many organizations that have invested in a CDC
streaming ingestion tool will need data replication abilities as well that their current technology cannot
accommodate. On the flip side, those organizations that have invested in a CDC replication tool will
often find deficits with real-time transformation, data manipulation, aggregations, and correlation
capabilities within the ingestion pipe.
This leads to multiple tools, high cost, architectural complexity, and a real barrier to achieving
streaming analytics and a streamlined data architecture that can scale.
Finding a Data Integration solution that offers CDC Replication, Streaming ETL, and Batch in one single
pane of glass platform is the ideal scenario as you look to incorporate streaming into your Data
Architecture to drive streaming analytics.
7. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Once Streaming Data Is In Place, What Can Companies
Do With Real-Time Data Analytics?
Real-time data analytics are already used by banks to detect potential fraud.
Financial institutions monitor how and where customers use their cards, and if
something doesn't look quite right, artificial intelligence algorithms will
automatically detect the potential fraud and send out an alert.
Websites and apps also use real-time data to monitor prospects’ locations and
offer appropriate products and services. If you’re at an airport, for example, it
might be the perfect time to show you an ad for travel insurance.
8. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Once Streaming Data Is In Place, What Can Companies
Do With Real-Time Data Analytics?
Erez Alsheich also notes, "Organizations can offer immediate, detailed credit
assessments, so they can reject or approve loans in real-time. This could
revolutionize the consumer loan market.”
Education is also an industry that is ripe for disruption. Once we move to a
hybrid education model in which a portion of the curriculum is delivered by AI-
enabled systems, we can personalize the education journey with real-time data
processing. Companies can customize the sequence and selection of math and
language questions that are served to students based on their individual needs
and previous responses.
9. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
How Organizations Can Get Ready For Real-Time Data
Analytics
Choose the right use case. Pick one specific use case in your organization that could
benefit immediately from having real-time data. Where would you get a high ROI from
having the lowest possible latency in near real-time?
Figure out how you’re going to get data. In order to get the most value from real-time
analytics, companies need to have streaming data ingestion with modern, multi-modal
change data capture in place.
Design for real-time analytics. “Streaming data analytics requires a paradigm shift,”
says Alsheich. Instead of trying to implement older batching-style strategies in real time,
you have to design your systems to look for changes in the data in real time. Then you will
need to have the right infrastructure in place to process that data as you stream it.
10. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Get Ready For The Real-Time Revolution
As our world becomes more data-driven, streaming and real-time analytics
become increasingly important for businesses.
All of the world’s most successful companies (like Google, LinkedIn, Facebook,
and Amazon) have integrated real-time analytics systems into their models, so
they can leverage big data to connect with their customers and maximize sales.
Your company can be next, and these tips can help you prepare for the real-
time revolution.
To learn more about how to get your company ready for streaming analytics,
check out my full interview with Erez Alsheich of Equalum.
11. © 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Learn More About Change Data Capture
‘Top Design and Implementation Challenges with Change Data Capture”
READ MORE - https://hubs.la/H0JYzJ50
12. Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2020 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2020 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
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