Product, technology, and R&D professionals are always keen to discuss how software companies are driving product innovation and new revenue streams through embedded analytics. At a special in-person event at the Sisense offices in Tel Aviv, a select group of product, technology and R&D professionals gathered to talk about how data has become a key point of differentiation for product offerings, how software companies that deliver analytics and insights to customers see better customer engagement and satisfaction, and how they enjoy increased revenues.
Topics covered included the opportunities presented by AWS’ new “Lake House” architecture, the benefits of pairing the right cloud solution with the right custom analytics platform, and how actionable intelligence from cloud sources can take a company’s embedded analytics to exciting new places.
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AWS Lake House architecture: Simpler storage, faster insights
Insights embedded into applications have to come from somewhere, and cloud services (especially those at AWS) are always changing. To drive this point home, Yonatan Dolan, an Analytics Specialist from AWS, introduced AWS’ new Lake House architecture. This cutting-edge service integrates the abilities of a data lake, a data warehouse, and purpose-built stores, to enable unified governance and easy data movement. Lake House’s unique architecture on AWS stores data in a data lake and gives users access to a ring of purpose-built services around the lake that empower them to make decisions faster, at scale, and with high performance.
Yonatan demonstrated that as data volumes increase (at an unprecedented rate), this approach is gaining traction in order to handle vast amounts of data, aggregate it all into a single location, and apply analytics (including machine learning) to it to derive actionable intelligence from both structured and unstructured data more effectively.
Infusing embedded analytics into customer-facing apps, products, and experiences is a key way for companies to skyrocket their businesses to the next level.
“This is a really exciting time for Sisense, AWS, and the analytics world as a whole,” said Aviad Harell, Sisense co-founder, COO, and GM Israel. “The potential for apps that embed analytics is limitless. Customers are demanding analytics, and companies are realizing the value of their data. Evolution in every industry will be driven by this trend. It’s awesome to see so many are so eager to learn about the potential that analytics powered by data from their AWS cloud solutions can provide.”
A winning team: AWS cloud and Sisense
Lake House is just the latest in a long line of AWS cloud products that companies can use to derive insights that will power their in-app analytics. We follow new AWS products very closely here at Sisense.
As a certified AWS Data and Analytics Competency partner as well as an AWS Independent Software Vendor Accelerate and Marketplace partner, Sisense is the custom analytics platform for connecting to AWS cloud products. Our cloud-native platform is uniquely well suited for a comprehensive list of Amazon databases, platforms, and cloud storage services, such as Amazon DocumentDB, Amazon Aurora, Amazon DynamoDB, Amazon S3, Amazon Redshift, Amazon Athena, Amazon Kinesis, Amazon SageMaker, Amazon Comprehend, and AWS Outposts.
Pairing the right analytics platform with the right AWS cloud product is one way organizations of all kinds can accelerate and future-proof their data strategy, infusing advanced real-time intelligence into customer-facing apps.
“The full range of Sisense features allows businesses to analyze all their data,” said Assaf Jacoby, Sisense AVP of Cloud Alliances. “It also empowers them to increase analytics adoption internally, create new business value and revenue streams, and adapt to changing business requirements.”
Derive actionable intelligence from AWS cloud sources, evolve your business
If your company uses an AWS cloud solution, the logical next step for product teams trying to embed analytics is to pick a platform that will get actionable intelligence from that cloud data storage location into the core product. Understanding embedded analytics best practices will make this process much smoother.
Eitan Sofer, Sisense Director of Developer Experience in the product division, explained that these teams need to grapple with a slew of questions, including:
- How well can embedded analytics from a third-party provider be integrated into an existing product?
- Can you customize the look, feel, and performance of your embedded analytics?
- Will the solution scale to any number of users with high performance?
- Does the solution offer high security and easy governance?
- What kind of support will you have during the go-to-market phase?
“Data and analytics make everyone perform better. Infusing analytics into customer-facing products or internal systems and processes helps users of all kinds make smarter, data-driven decisions,” said Eitan. “And platforms like Sisense that empower companies to perfectly match their app’s look and feel while delivering custom analytics and visualizations truly help evolve products and companies, especially with intelligence drawn from cutting-edge cloud solutions like the ones AWS provides.”
Excited to transform your business with embedded analytics? Check out this special report from Constellation about the next generation of embedded analytics.
Adam Murray is a marketing content writer and manager at Sisense, focusing on technology, CRM, satellite communications, and much more. He’s previously worked for Amdocs, Gilat Satellite Systems, and Allot Communications. When not spending time with his wife and son, Adam can be found cheering on the Tottenham Hotspur.