Applied Data & Analytics

Chairpersons welcome and opening remarks. 

To follow soon …

• Every company needs BI, but BI alone is not enough. 
• To be truly data-driven, companies also need to operationalize their data. 
• With cloud warehouses and reverse ETL, getting enriched data back to business platforms is now easy. 
• Getting data back to your business teams is the key to being truly data-driven. 

Traditional Data Governance focuses squarely on mitigating risk. But with a risk focus, companies miss important opportunities to capture value from their data. Learn how to use mature Data & Information Governance as a framework to balance risk and business opportunity to drive innovation, promote data-driven decisions, and enhance corporate success in a world of risk.

• Understanding the real value of data before trying to add a price tag to deliverables.  
• How to measure data through KPI’s – creating a holistic business strategy where data is part of the chain.  
• Discoverability and data quality – the key pillars for being able to action and monetize capabilities.   
• Being adaptable and open to innovation.

For decades, businesses have aspired to be ‘data-driven’. What does being ‘data-driven’ really mean? Surely it’s got to mean more than everyone staring at dashboards…more than everyone having access to the latest release of Microsoft Excel…more than everyone in an organization being able to query data… more than an organization spinning up a modern data stack. Even if all of the above were true, it begs the question ‘So what?’

That’s the problem with chasing ‘data-drivenness’ – it sort of means nothing. We contend that businesses must focus on synchronizing their business processes with data and have a clear objective to pursue -minimizing the delay between when the data suggests an opportunity to optimize and when the business is able to act on the same. At one extreme, we have recommendation engines and online ad serving systems that operate at near real-time – given the characteristics of the situation, these algorithms serve up content that optimizes revenue for the business.

We also note how traditionally brick-and-mortar big box retailers have been forced to rethink the timescales at which they fulfill inventory or run promotions in response to the speed at which large, fully online retailers are able to operate. What is happening is a sweeping trend to get business processes to move at the speed at which data intensive algorithms generate new insights. In this webinar, we discuss a blueprint for businesses to evolve to data-synchronized organizations using a modern data stack. We will explain why we view this transformation as one that’s readily accessible to organizations of all sizes, due to recent advances in analytical compute and storage, emergence of intuitive products coupled with the affordable economics of SaaS. We will cover how Sigma’s Workbooks are the center of driving this transformation in businesses across industry verticals.

Most organizations recognize the importance of trusting their data. After all, you want to feel confident that your data is accurate, high-quality, and can be used to drive positive business decisions. So what can you do to gain that trust? At MANTA, we’re ready to show you.

During this presentation, Joe Chmielewski, Team Lead, Solutions Engineer at MANTA, will break down why data lineage is the key to gaining trust in your data. In just 20 minutes, he will:

• Explain what data lineage is and why you need it

• Demonstrate how data lineage enables trust in data assets

• Highlight key data lineage use cases

• Perform a live demo of MANTA’s automated data lineage platform

• Organizations have scaled up their investments in Big Data and AI, however, a majority of key data and analytics executives report that business adoption of Data and AI initiatives still pose a major challenge.
• Adoption is often the last step in the analytics value chain and the insights gained from these analytics initiatives often fail to drive action.
• In this presentation, we will deep dive into the key challenges causing this gap between insights and impact in an organization and discuss recommendations to bridge the same.

To follow soon …

Today, data lakes are widely used and have become extremely affordable as data volumes have grown. However, they are only meant for storage and by themselves provide no direct value. With up to 80% of data stored in the data lake today, how do you unlock the value of the data lake? The value lies in the compute engine that runs on top of a data lake.

During this session, Ahana Product Manager Rohan Pednekar will discuss how to unlock the value of your data lake with the emerging Open Data Lakehouse architecture and why Presto, the open source SQL query engine, is critical to this approach. Finally, he will show why Ahana Cloud is the easiest way to deploy and run Presto on AWS S3.

• Identifying target-rich, high-value data that can be used to generate intelligence. 
• Transitioning from big data to ‘right’ data analytics – how to dissect the data you need. 
• Collection, storage, exchangeability and security – how to ensure optimised processing of data for optimum response and actions. 
• Data as the core of digital – aligning strategies to maximise data capabilities.