We are a leading provider of self-service data analytics software. Our software
platform enables organizations to dramatically improve business outcomes and
the productivity of their business analysts. Our subscription-based platform
allows organizations to easily prepare, blend, and analyze data from a multitude
of sources and more quickly benefit from data-driven decisions. The ease-of-use,
speed, and sophistication that our platform provides is enhanced through intuitive
and highly repeatable visual workflows. We aim to make our platform as ubiquitous
in the workplace as spreadsheets are today.
As the volume, velocity, and variety of data continue to expand, the ability
to leverage this data for actionable insights has become increasingly foundational
to modern business success. However, traditional data analysis tools and processes
are slow, difficult to use, and resource-intensive, often requiring multiple
steps by data analysts, data scientists, information technology, or IT, employees,
and other data workers to complete even the most basic analysis. As a result,
these tools and processes are unable to keep pace with the rapid analytics demanded
by organizations today.
Our platform democratizes access to data-driven insights by expanding the capabilities
and analytical sophistication available to all data workers, ranging from business
analysts to expert programmers and trained data scientists. We bring the fragmented
analytic process into one simple and cohesive self-service experience, combining
tasks that were previously distributed among multiple tools and parties. Our
platform allows a single user to access various data sources, clean and prepare
data, perform a variety of analyses, and then deploy the results for consumption
and to operationalize the insights discovered. This is done through visual workflows
and an intuitive drag-and-drop interface that can eliminate the need to write
code and reduce tedious, time-consuming tasks to a few mouse-clicks. The resulting
opportunity is significant, as our platform can enable millions of underserved
data workers to more effectively do their jobs.
Organizations of all sizes and across a wide variety of industries have adopted
our platform. As of December 31, 2017, we had approximately 3,400 customers
in more than 70 countries, including over 400 of the Global 2,000 companies.
Our customers include Ford Motor Company, Kaiser Foundation Health Plan, Inc.,
Knight Transportation Inc., Nike, Inc., Southwest Airlines Co., Tableau Software,
Inc., and Tesco PLC. Our platform is also leveraged by leading management consulting
organizations such as Accenture plc, Bain & Company, and Boston Consulting
Group.
We employ a “land and expand” business model. Our go-to-market
approach often begins with a free trial and is followed by an initial purchase
of our platform offerings. As organizations realize the benefits derived from
our platform, use frequently spreads across departments, divisions, and geographies
through word-of-mouth, collaboration, and standardization of business processes.
Over time, many of our customers find that the use of our platform is more strategic
in nature and our platform becomes a fundamental element of their regular analytical
processes.
Our self-service data analytics platform disrupts well-established portions
of the business analytics software market. According to IDC, the worldwide market
for big data and analytics software represented approximately $49 billion in
2016 and is expected to grow to approximately $81 billion in 2021. Within the
broader big data and analytics software market, our solutions currently address
the business intelligence and analytic tools, analytic data integration and
spatial information analysis markets, which collectively represented approximately
$19 billion in 2016 and are expected to grow to approximately $29 billion in
2021.
There is significant additional potential spend not included in the above estimates
associated with spreadsheet users who we believe can benefit from our platform.
According to a separate IDC study that we commissioned, an estimated 21 million
spreadsheet users worldwide worked on advanced data preparation and analytics
in 2016. Based on this study, we estimate that there is an additional opportunity
of over $10 billion that our platform can address. In the same study, IDC estimated
that over 80% of spreadsheet users are using manual copy and paste methods to
acquire data. The IDC study also estimated that in the United States alone,
there is a cost to companies of approximately $60 billion per year associated
with time spent by data workers repeating processes when data sources are updated.
Our analytics platform enables organizations to dramatically improve business
outcomes and the productivity of their business analysts and citizen data scientists.
Our subscription-based platform allows organizations to easily profile, prepare,
blend, and analyze data from a multitude of sources and benefit from data-driven
decisions. Our platform is:
• Efficient. We offer a self-service platform that allows business analysts
to perform analysis on their own that traditionally required multiple parties
and work streams to complete. Our in-memory software “engine” is
designed to ingest and process large volumes of data rapidly and enable responsive
and agile analysis, delivering dramatically “faster time to insights”.
Once a workflow has been assembled, the analysis can be repeated in minutes
and shared with others who can easily replicate the analysis. With our platform,
data analysis is automated, repeatable, and shareable.
• Independent. We enable business analysts to rapidly answer challenging
business questions on their own, without the need for support from expert programmers,
trained data scientists, or other members of the IT department. Our platform
offers analytics with easily understandable drag-and-drop tools that have easy-to-configure
parameters that do not require coding. With our platform, business analysts
can manage all steps in an analytic process without the assistance of their
IT departments.
• Flexible. Our platform does not require a pre-packaged, static data
set and instead allows the user to create a visual workflow to securely interact
with the underlying source data. Workflows can be easily changed and reconfigured
to iterate an analysis and add a new data source or new logic. They also can
be easily adapted to conform with changes in the underlying data to repeat the
analysis. This flexibility allows workflows to be configured to address a wide
range of use cases. Business analysts can build apps that let others interact
with the workflow through a simple interface available on the public or private
cloud or they can configure a workflow to output results directly to a database
or system of record. Our platform also outputs to most visual formats such as
those offered by Microsoft Corporation, Qlik Technologies, Inc., and Tableau.
• Sophisticated. Our platform provides business analysts an extensive
set of analytical capabilities. Our drag-and-drop visual workflow environment
includes capabilities that allow users to: access data from a variety of locations
such as a local desktop, a relational database, or the cloud; prepare data for
analysis; blend multiple data sources regardless of the data structure or format,
including big data technologies; gain access to over 50 pre-packaged tools of
the most widely used procedures for predictive analytics, grouping, and forecasting;
and take advantage of geospatial data to drive understanding of topics such
as trade areas and drive-time analysis.
• Scalable. Our platform offers a secure collaboration environment for
even the largest organizations. Business analysts can create, publish, and share
analytic applications across the organization, embed analytic processes into
other internal applications, and save and access workflows within a centralized
repository with version control when working across multiple teams. The ability
to deploy our platform on-premise or in the cloud also provides additional flexibility
to scale as each customer’s business needs grow. By pushing analytical
workloads to a reliable server architecture, customers can run sophisticated
compute-intensive processes more efficiently than local machines allow, while
automating and scheduling these workflows to give business analysts stronger
control of their analytic landscape.
In-Memory Engine
Our in-memory engine is optimized to process data within RAM and can utilize
disk, when necessary, as temporary virtual memory. This facilitates significantly
faster and more secure processing of data than traditional disk-based mechanisms
while ensuring that the source data remains unaltered and is not duplicated.
Key features of our engine include:
• Connected. Business analysts can rapidly connect to data in existing
formats and locations, reducing the need for time-consuming data transformation
processes that typically require IT personnel.
• Non-persisted. Our engine leverages non-persisted data pipelines to
enable users to process large amounts of data securely while applying complex
logic every time they run an analytic workflow.
• Scaled-out. While most workflows can be run on any single desktop
or laptop, when greater processing capability is required, workloads can be
pushed to a server or cluster of servers, including Hadoop or Spark clusters.
In addition to our high speed in-memory processing capabilities, our platform
enables in-database processing to take advantage of computing resources where
the data resides for certain use cases.
Sophisticated Analytic Models
We enable business analysts to run analytics ranging from basic to highly complex,
including predictive, prescriptive, and spatial analytics. Specifically, we
enable predictive analytics through utilization of R, an open source programming
language and software environment for statistical computing, and Python, a popular
programming language for analytics with many publicly available packages. Our
capabilities allow transparency and editing of the R and Python code without
requiring prior coding experience. In addition, in-database processing enables
analysts to scale predictive analytics and harness the value of large sets of
data without moving the data out of a database, improving predictive model development
performance over traditional approaches. Deep geo-spatial tools, such as a drive
time engine, create the basis for performing location-based analysis.
Open and Modular Core
Our platform is built with an open and modular core that enables additional
functions and programming models to interact with it. For example, our platform
can utilize R for advanced analytics while providing a simple drag-and-drop
interface that abstracts the complexity of the underlying code. For sophisticated
business analysts, the underlying code is available for review and adjustment.
The integration of our platform and R takes advantage of segmented, but integrated
main-memory resources to ensure seamless, fast operations. More recently, we
introduced the JavaScript V8 engine for our platform in a similar capacity.
This enables the introduction of new HTML5 UI, Server-side Javascript, and JSON/REST
APIs to all fuel the innovation being driven from our platform.
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