Data Warehouse Embedded Analytics Presentation 
Sisense
JULY 8, 2020
Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.
Sisense
NOVEMBER 30, 2020
The smart ones are finding new ways to monetize their data, either by embedding analytics into apps and services that existing users will pay for or using them to grow their audience and expand into new markets. Data-driven apps: Giving users the information they crave. Eitan is also an avid music fan and surfer.
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Sisense
JULY 6, 2021
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. See our free analyst report on next-generation embedded custom analytics. “The potential for apps that embed analytics is limitless.
Sisense
MAY 11, 2021
In determining how we wanted to merge these data stacks and how we wanted to model our data, we also revisited our data strategy to consider what we as a data team were striving to achieve within the business. The right data model + artificial intelligence = augmented analytics. Dig into AI.
Sisense
OCTOBER 14, 2020
Today, data teams form a foundational element of startups and are an increasingly prominent part of growing existing businesses because they are instrumental in helping their companies analyze the huge volumes of data that they must deal with. Developing data maturity and anticipating growth.
Data Pine
NOVEMBER 11, 2021
a) Data Connectors Features. b) Analytics Features. For a few years now, Business Intelligence (BI) has helped companies to collect, analyze, monitor, and present their data in an efficient way to extract actionable insights that will ensure sustainable growth. c) Join Data Sources. Table of Contents.
Sisense
MARCH 14, 2021
For starters, the rise of the Internet of Things (IoT) has created immense volumes of new data to be analyzed. IoT sensors on factory floors are constantly streaming data into cloud warehouses and other storage locations. The pressure to adopt the edge computing paradigm increases with the number of sensors pouring out data.
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