Datastax - The Architect's guide to customer experience (CX)DataStax
From scalability to data access to data governance, learn the specific performance and data requirements of a customer experience-ready data management platform.
Active Governance Across the Delta Lake with AlationDatabricks
Alation provides a single interface to provide users and stewards to provide active and agile data governance across Databricks Delta Lake and Databricks SQL Analytics Service. Understand how Alation can expand adoption in the data lake while providing safe and responsible data consumption.
Tomasz Tunguz - 10 Learnings from Redpoint 2020 GTM SurveySaaStock
Glean insights into the current state of Go-to-Market Strategy through a data-driven analysis led by Tomasz Tunguz, Managing Director at Redpoint Ventures. This presentation will outline the Top 10 learnings from the Redpoint 2020 GTM Survey and provide a snapshot of the best practices performed by industry leaders across growth stages. What are the most common structures for sales, account executives, and development representatives teams? How much of your ARR should be spent on marketing programs? What gross margin payback period should you be targeting? These questions and more will be answered in a cohort analysis of over 500 companies.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
In their webinar "Big Data Fabric 2.0 Drives Data Democratization" Ben Szekley, Cambridge Semantics’ SVP of Field Operations, and guest speaker, Forrester’s Noel Yuhanna, author of the Forrester report: “Big Data Fabric 2.0 Drives Data Democratization”, explored why data-driven businesses are making a big data fabric part of their data strategy to minimize data complexity, integrate siloed data, deliver real-time trusted insights, and to create new business opportunities. These are the slides from that webinar.
Datastax - The Architect's guide to customer experience (CX)DataStax
From scalability to data access to data governance, learn the specific performance and data requirements of a customer experience-ready data management platform.
Active Governance Across the Delta Lake with AlationDatabricks
Alation provides a single interface to provide users and stewards to provide active and agile data governance across Databricks Delta Lake and Databricks SQL Analytics Service. Understand how Alation can expand adoption in the data lake while providing safe and responsible data consumption.
Tomasz Tunguz - 10 Learnings from Redpoint 2020 GTM SurveySaaStock
Glean insights into the current state of Go-to-Market Strategy through a data-driven analysis led by Tomasz Tunguz, Managing Director at Redpoint Ventures. This presentation will outline the Top 10 learnings from the Redpoint 2020 GTM Survey and provide a snapshot of the best practices performed by industry leaders across growth stages. What are the most common structures for sales, account executives, and development representatives teams? How much of your ARR should be spent on marketing programs? What gross margin payback period should you be targeting? These questions and more will be answered in a cohort analysis of over 500 companies.
Modernizing to a Cloud Data ArchitectureDatabricks
Organizations with on-premises Hadoop infrastructure are bogged down by system complexity, unscalable infrastructure, and the increasing burden on DevOps to manage legacy architectures. Costs and resource utilization continue to go up while innovation has flatlined. In this session, you will learn why, now more than ever, enterprises are looking for cloud alternatives to Hadoop and are migrating off of the architecture in large numbers. You will also learn how elastic compute models’ benefits help one customer scale their analytics and AI workloads and best practices from their experience on a successful migration of their data and workloads to the cloud.
In their webinar "Big Data Fabric 2.0 Drives Data Democratization" Ben Szekley, Cambridge Semantics’ SVP of Field Operations, and guest speaker, Forrester’s Noel Yuhanna, author of the Forrester report: “Big Data Fabric 2.0 Drives Data Democratization”, explored why data-driven businesses are making a big data fabric part of their data strategy to minimize data complexity, integrate siloed data, deliver real-time trusted insights, and to create new business opportunities. These are the slides from that webinar.
Snowflake: The Good, the Bad, and the UglyTyler Wishnoff
Learn how to solve the top 3 challenges Snowflake customers face, and what you can do to ensure high-performance, intelligent analytics at any scale. Ideal for those currently using Snowflake and those considering it. Learn more at: https://kyligence.io/
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
Apache Kafka and the Data Mesh | Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Data centric business and knowledge graph trendsAlan Morrison
The deck for my kickoff keynote at the Data-Centric Architecture Forum, February 3, 2020. Includes related data, content, and architecture definitions and fundamental explanations, knowledge graph trends, market outlook, transformation case studies and benefits of large-scale, cross-boundary integration/interoperation.
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Here's the deck we used for our Series-A round. We raised $26M led by Benchmark, 2 months after our Seed round with Accel.
Even though we didn't necessarily show the appendix slides, we sent them along with the rest of the deck.
See https://airbyte.com
BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? This session was delivered for SharePoint Saturday Reston.
At wetter.com we build analytical B2B data products and heavily use Spark and AWS technologies for data processing and analytics. I explain why we moved from AWS EMR to Databricks and Delta and share our experiences from different angles like architecture, application logic and user experience. We will look how security, cluster configuration, resource consumption and workflow changed by using Databricks clusters as well as how using Delta tables simplified our application logic and data operations.
Building Lakehouses on Delta Lake with SQL Analytics PrimerDatabricks
You’ve heard the marketing buzz, maybe you have been to a workshop and worked with some Spark, Delta, SQL, Python, or R, but you still need some help putting all the pieces together? Join us as we review some common techniques to build a lakehouse using Delta Lake, use SQL Analytics to perform exploratory analysis, and build connectivity for BI applications.
Logical Data Fabric: Architectural ComponentsDenodo
Watch full webinar here: https://bit.ly/39MWm7L
Is the Logical Data Fabric one monolithic technology or does it comprise of various components? If so, what are they? In this presentation, Denodo CTO Alberto Pan will elucidate what components make up the logical data fabric.
Power BI Overview, Deployment and GovernanceJames Serra
Deploying Power BI in a large enterprise is a complex task, and one that requires a lot of thought and planning. The purpose of this presentation is to help you make your Power BI deployment a success. After a quick Power BI overview, I’ll discuss deployment strategies, common usage scenarios, how to store and refresh data, prototyping options, how to share externally, and then finish with how to administer and secure Power BI. I’ll outline considerations and best practices for achieving an optimal, well-performing, enterprise level Power BI deployment.
Data Marketplace and the Role of Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3IS9sQS
A data marketplace is like an online shopping interface specializing in data. Ideally, it should work just like an online store, with minimal latency and maximum responsiveness. However, this does not mean that all of the data in the data marketplace needs to be stored in the same central repository.
In this session, Shadab Hussain, Americas Sales Head, Data Analytics at Wipro, a partner company with Denodo and a co-sponsor of DataFest 2021, talks about the role of data virtualization in enabling full-featured data marketplaces. Such data marketplaces provide real-time, curated access to data, even when the data is stored across many different sources throughout the organization.
You will learn:
- The main features of a data marketplace
- Why organizations need data marketplaces
- Why data marketplaces sometimes fail
- How data virtualization enables the most effective data marketplaces
- How one of Europe’s premiere public healthcare system organizations leveraged a data marketplace to improve data consumption and ease of access
Making the Case for Legacy Data in Modern Data Analytics PlatformsPrecisely
Modern data analytics platforms that fuel enterprise-wide data hubs are critical for decision making and information sharing. The problem? Integrating legacy data stores into these hubs is just plain hard, and there is no magic bullet. However, the best data hubs include ALL enterprise data.
So how can you ensure that you are building the best modern data analytics platform possible?
Join this webinar to learn more on:
- Best practices for integrating legacy data sources, such as mainframe and IBM i, into modern data analytics platforms such as Cloudera, Databricks, and Snowflake
- How Syncsort Connect customers are incorporating legacy data sources into enterprise data hubs to inform strategic use cases such as claims, banking, and shipping experiences
Battery Ventures State of the OpenCloud Report 2022Battery Ventures
Battery Ventures' 2022 State of the OpenCloud report, compiled by General Partner Dharmesh Thakker and his team Danel Dayan, Jason Mendel and Patrick Hsu. The report analyzes the macro technology and economic trends impacting the cloud market, and provides advice for cloud-native entrepreneurs who are navigating these trends to build large, enduring businesses.
MT13 - Keep your business processing operating at peak efficiency with Dell E...Dell EMC World
Big Data comes from somewhere! Chances are, the largest contributor to the data deluge in your world are your own main business processing systems. It’s critical to employ the highest efficiency possible when deploying Microsoft SQL, Oracle, or SAP database platforms for business processing. Join this session to find out more about Dell Engineered Solutions for Databases, and grow your data engines on your terms!
Snowflake: The Good, the Bad, and the UglyTyler Wishnoff
Learn how to solve the top 3 challenges Snowflake customers face, and what you can do to ensure high-performance, intelligent analytics at any scale. Ideal for those currently using Snowflake and those considering it. Learn more at: https://kyligence.io/
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
Apache Kafka and the Data Mesh | Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Data centric business and knowledge graph trendsAlan Morrison
The deck for my kickoff keynote at the Data-Centric Architecture Forum, February 3, 2020. Includes related data, content, and architecture definitions and fundamental explanations, knowledge graph trends, market outlook, transformation case studies and benefits of large-scale, cross-boundary integration/interoperation.
Overview of Business Analytics and career lessons learnt / advice. Presentation delivered to Melbourne Business School - Masters of Business Analytics - July 2016.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Here's the deck we used for our Series-A round. We raised $26M led by Benchmark, 2 months after our Seed round with Accel.
Even though we didn't necessarily show the appendix slides, we sent them along with the rest of the deck.
See https://airbyte.com
BI: new of the buzz words that everyone is talking about but what is it? How can it be used to make a impact in my organization? How do I get started? This session was delivered for SharePoint Saturday Reston.
At wetter.com we build analytical B2B data products and heavily use Spark and AWS technologies for data processing and analytics. I explain why we moved from AWS EMR to Databricks and Delta and share our experiences from different angles like architecture, application logic and user experience. We will look how security, cluster configuration, resource consumption and workflow changed by using Databricks clusters as well as how using Delta tables simplified our application logic and data operations.
Building Lakehouses on Delta Lake with SQL Analytics PrimerDatabricks
You’ve heard the marketing buzz, maybe you have been to a workshop and worked with some Spark, Delta, SQL, Python, or R, but you still need some help putting all the pieces together? Join us as we review some common techniques to build a lakehouse using Delta Lake, use SQL Analytics to perform exploratory analysis, and build connectivity for BI applications.
Logical Data Fabric: Architectural ComponentsDenodo
Watch full webinar here: https://bit.ly/39MWm7L
Is the Logical Data Fabric one monolithic technology or does it comprise of various components? If so, what are they? In this presentation, Denodo CTO Alberto Pan will elucidate what components make up the logical data fabric.
Power BI Overview, Deployment and GovernanceJames Serra
Deploying Power BI in a large enterprise is a complex task, and one that requires a lot of thought and planning. The purpose of this presentation is to help you make your Power BI deployment a success. After a quick Power BI overview, I’ll discuss deployment strategies, common usage scenarios, how to store and refresh data, prototyping options, how to share externally, and then finish with how to administer and secure Power BI. I’ll outline considerations and best practices for achieving an optimal, well-performing, enterprise level Power BI deployment.
Data Marketplace and the Role of Data VirtualizationDenodo
Watch full webinar here: https://bit.ly/3IS9sQS
A data marketplace is like an online shopping interface specializing in data. Ideally, it should work just like an online store, with minimal latency and maximum responsiveness. However, this does not mean that all of the data in the data marketplace needs to be stored in the same central repository.
In this session, Shadab Hussain, Americas Sales Head, Data Analytics at Wipro, a partner company with Denodo and a co-sponsor of DataFest 2021, talks about the role of data virtualization in enabling full-featured data marketplaces. Such data marketplaces provide real-time, curated access to data, even when the data is stored across many different sources throughout the organization.
You will learn:
- The main features of a data marketplace
- Why organizations need data marketplaces
- Why data marketplaces sometimes fail
- How data virtualization enables the most effective data marketplaces
- How one of Europe’s premiere public healthcare system organizations leveraged a data marketplace to improve data consumption and ease of access
Making the Case for Legacy Data in Modern Data Analytics PlatformsPrecisely
Modern data analytics platforms that fuel enterprise-wide data hubs are critical for decision making and information sharing. The problem? Integrating legacy data stores into these hubs is just plain hard, and there is no magic bullet. However, the best data hubs include ALL enterprise data.
So how can you ensure that you are building the best modern data analytics platform possible?
Join this webinar to learn more on:
- Best practices for integrating legacy data sources, such as mainframe and IBM i, into modern data analytics platforms such as Cloudera, Databricks, and Snowflake
- How Syncsort Connect customers are incorporating legacy data sources into enterprise data hubs to inform strategic use cases such as claims, banking, and shipping experiences
Battery Ventures State of the OpenCloud Report 2022Battery Ventures
Battery Ventures' 2022 State of the OpenCloud report, compiled by General Partner Dharmesh Thakker and his team Danel Dayan, Jason Mendel and Patrick Hsu. The report analyzes the macro technology and economic trends impacting the cloud market, and provides advice for cloud-native entrepreneurs who are navigating these trends to build large, enduring businesses.
MT13 - Keep your business processing operating at peak efficiency with Dell E...Dell EMC World
Big Data comes from somewhere! Chances are, the largest contributor to the data deluge in your world are your own main business processing systems. It’s critical to employ the highest efficiency possible when deploying Microsoft SQL, Oracle, or SAP database platforms for business processing. Join this session to find out more about Dell Engineered Solutions for Databases, and grow your data engines on your terms!
Ways to Make Business Intelligence Work for Your Small BusinessSpiceworks
In this first 60-minute webinar in the series, Spiceworks and CDW team up to provide answers to your questions on business intelligence - a subject that's becoming increasingly important to small businesses.
Hybrid IT: The Importance of Integration to Salesforce SuccessDarren Cunningham
Are you struggling to integrate Salesforce with other systems? Are you looking for ways to get more from both cloud and on-premise investments? According to IDC research, “IT organizations are looking for ways to improve cloud governance and control, while also ensuring business continuity and continued innovation.” This session will feature three case studies outlining best practices and examples of how the right approach to data integration can accelerate Salesforce adoption and ROI. This session is brought to you by Informatica, a proud sponsor of Dreamforce.
These slides - based on the webinar - shed light on how business stakeholders make the most of information from their big data environments and the requirements those stakeholders have to turn big data into business impact.
Using recent big data end-user research from leading IT analyst firm Enterprise Management (EMA), data from Vertica’s recent benchmarks on SQL on Hadoop, and firsthand customer experiences, viewers will learn:
- Use cases where end users around the world are using big data in their organizations
- How maturity with big data strategies impact why and how business stakeholders use information from their big data environments
- How Vertica empowers the use of information from big data environments
These slides--based on the webinar--from leading IT analyst firm Enterprise Management Associates (EMA) and Attunity provide insights into how organizations are overcoming inherent challenges to enable SAP data-driven initiatives and meet the analytics goals of their organization with modern data integration and management.
Turning Big Data into Better Business OutcomesCisco Canada
The big data era is upon us as organizations are awash in social, mobile and machine-generated data. Opportunity abounds. But competition threatens. Further this high volume, data-at-the-edge environment challenges centralized data warehouse approaches typical with BI and Analytics today. Data virtualization provides a more agile, leave-the-data-where-it-lies way to fulfill BI and Analytic needs and achieve key business outcomes.
Building Resiliency and Agility with Data Virtualization for the New NormalDenodo
Watch: https://bit.ly/327z8UM
While the impact of COVID-19 is uniform across organisations in the region, a lot of how the organisation can recover from the impact and strive in the market would depend on their resiliency and business agility. An organisation’s data management strategy holds the key, as they tackle the challenges of siloed data sources, optimising for operational stability, and ensuring real time delivery of consistent and reliable information, irrespective of the data source or format.
Join this session to hear why large organisations are implementing Data Virtualization, a modern data integration approach in their data architecture to build resiliency, enhance business agility, and save costs.
In this session, you will learn:
- How to deliver clear strategy for agile data delivery across the enterprise without pains of traditional data integration
- How to provide a robust yet simple architecture for data governance, master data, data trust, data privacy and data access security implementation - all from single unified framework
- How to deploy digital transformation initiatives for Agile BI, Big Data, Enterprise Data Services & Data Governance
Achieving digital business requires not just traditional workload automation, but automation that spans operations, development, and business functions. Digital business success requires Digital Business Automation.
Check out these slides from the webinar featuring Dan Twing, president and COO of leading IT analyst firm Enterprise Management Associates (EMA), and Tim Eusterman, senior director solutions marketing at BMC, to discover why automation is at the core of digital business success.
Harnessing the power of data for competitive advantage with MicroStrategy Enterprise Analytics. This presentation was given at the Florida MicroStrategy User Group Meeting on September 17th, 2015. To learn more about these meetings, join the user group on LinkedIn at https://www.linkedin.com/groups/MicroStrategy-Florida-User-Group-8393233/about
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Transforming Devon’s Data Pipeline with an Open Source Data Hub—Built on Data...Databricks
How did Devon move from a traditional reporting and data warehouse approach to a modern data lake? What did it take to go from a slow and brittle technical landscape to an a flexible, scalable, and agile platform? In the past, Devon addressed data solutions in dozens of ways depending on the user and the requirements. Through a visionary program, driven by Databricks, Devon has begun a transformation of how it consumes data and enables engineers, analysts, and IT developers to deliver data driven solutions along all levels of the data analytics spectrum. We will share the vision, technical architecture, influential decisions, and lessons learned from our journey. Join us to hear the unique Databricks success story at Devon.
2. Company Overview
~1,000 customers in 50 countries; SMBs to Fortune 100
99% net renewal from existing customers
100% year over year revenue growth for 5 consecutive years
$100m funding from top tier VC’s: Bessemer Ventures, DFJ Growth, Battery Venture
Numerous customer and industry awards; recognition from leading press
SIMPLIFYING business analytics for COMPLEX data
Preferred
Vendor MQ
Ventana Celestica CIO
“Takes disruption to a
whole new level”
“Creatinga Stir in
the World of BI”
“Taking Big Data
Analyticsby Storm”
Press:
Awards:
4. Data Complexity
Ease&AgilitySimplifying business analytics for complex data
Modern Self-
Service Tools
Legacy
Tools
Sisense
SIMPLIFYING
Single tool - data to dashboard
Deployed in days without IT
100% designed for business
Immediate insights
COMPLEX
Mash-up disparate sources
Large data sets (terabytes)
5. Impact
Pitfalls of traditional business analytics solutions
Data Complexity
DegreeofDifficulty
Lengthy Data Prep Can’t get immediate answers
High TCO for complex dataLimited Data Access
Hidden Costs
Overly dependent on IT
6. To address these pitfalls you need many things:
Sisense Delivers
Beautiful
Dashboards
Powerful Analytics Library of
Connectors
BUT WHAT SETS US APART IS
OUR SECRET SAUCE
7. Sisense Single StackTM and In-ChipTM changed the playing
field Single-Stack™
In-Chip™ Analytics
Visualization
DATA
ETL BI DB AnalyticsAD-HOCData Prep
SIMD ColumnarDataStore CPU Cache Entire MemoryHierarchy CrowdAccelerated
8. Business analytics is much more than visualization
Visualization
IT Workload
With Sisense: Free yourself
from dependence on IT
No need to remodel data
No need for DBA or consulting
No need to aggregate data
First Dashboard
Our Difference
In 90 Minutes
9. Agility to react quickly is critical to success
With Sisense: Immediate
answer to any question
No need to pre-define questions
No need to aggregate data
Full granular detail
Skip IT, when new questions arise
®Gartner
Top #2 By
Business Benefit
10. A hodgepodge of tools is hard to
navigate
Sisense: quick & easy start; low cost
to maintain, even as complexity
growsNo need to integrate multiple tools
No need for other data prep tools
No need for data warehouse
Frost & Sullivan
Winner
Customer Value Leadership
11. Multiple
Data
Sources Sisense Engine Interactive Dashboards
XLS, CSV
MySQL, SQL Server
Hadoop
Cloud Apps
Cloud or On-
Premise
End to end solution for easy mash-up of data
sources
12. Multiple
Data
Sources Sisense Engine Interactive Dashboards
XLS, CSV
MySQL, SQL Server
Hadoop
Cloud Apps
End to end solution for easy mash-up of data
sources
ODB
C
API SDK
13. Laser focused on customer success
Measured and rewarded for NPS
Re-earn your business each year
Designated success manager
“I appreciate the partnership
I feel with Sisense.”
Becky McDonough | Director,SullivanCotter
Gartner
Ranked #2 By
®
Customer Retention