E69 - Eran Vanounou - 10x - 100x Faster Data Lake Analytics with Autonomous Indexing

Eran Vanounou is the CEO of Varada, a data lake acceleration
platform that enables business users and data platform teams to
seamlessly carry out analytics directly on their cloud data lake
without compromising on query performance. It’s all about agility
and flexibility -- No need to move data or model it to get any
insights that you may need.


Varada enables the fastest time big data analytics ensuring the
fastest possible business analytics and quickest go-to-market
time. It offers the perfect balance between performance,
scalability, time to market, and cost.


Varada CEO Eran has over 20+ years of extensive experience in
developing and running technology businesses. He is passionate
about the effective blend of technology, people, and business
dynamics to unleash incredible results.


Before joining Varada, Eran has held various leadership roles in
companies like LivePerson, NICE, Oracle, Sun Microsystems, and
other leading software and technology companies.


At LivePerson, Eran led a worldwide team that developed and took
to market LiveEngage, the world's leading cloud platform,
supporting over 2 billion consumers and generating over $200
million annually.


In this episode, Eran shares all about data lake analytics and
how you should be performing your analytics directly into data
lakes to speed up your business performance.


Here are the key points of discussion of this exclusive episode:


Why did Eran decide to transition from large MNCs to the
startup ecosystem in his career?

How was his journey of this transition?

Eran also shares some valuable advice for executives wanting
to follow this path and looking to take the risk of joining
startups.

What is data lake analytics, and what does it mean for your
data analytics platforms.

How can your data engineering teams and business teams take
advantage of data lakes?

As we are collecting more data than ever before, data lakes
are also becoming more important than ever before.

The way we should look at the modern data architecture in
terms of using data lakes and warehouses.

When and how to take advantage of both data lake and
warehouse.

Importance of having a data warehouse as well as the
drawbacks of data warehousing.

The shortcoming of data warehouses is exactly why it has
become increasingly more important to apply analytics directly
into data lakes.

How data lake analytics speeds up the performance of
analytics and provides faster and more precise insights.

The technology and infrastructure required to make data lake
analytics possible.

How Varada carries out the indexing of underlying extremely
large data sets for improved performance.



If you are a data leader frustrated with the performance of your
data lakes and want to find out how you should be structuring
your data lake and data warehouse, this is the episode you should
not miss!


BusinessAnalytics, DataAnalytics, DataLake, DataWarehousing,
BigDataAnalytics