MatrixExample.docx

MATRIX

Accenture

Forrester Research

CIO.com

Tableau Software

Description

Provides strategy, consulting, digital, technology and operations services. Accenture Analytics in particular, which is part of Accenture Digital provides digital marketing, analytics, and mobility services.

Offers a variety of services including syndicated research on technology as it relates to business, quantitative market research on consumer technology adoption as well as enterprise IT spending, research-based consulting and advisory services, events, workshops, teleconferences, and executive peer-networking programs.

Built to deliver CIO-focused news, features and commentary on emerging technologies and products, industry trends and research, innovation in the tech industry, and legal and regulatory implications of technology.

Revenue: $826.9M
Type: Public
Founding Date: 2003 in Seattle, WA
Number of Employees: 3,223

Source: Owler

Point 1

Early adopters are viewing big data as the catalyst for transforming their organizations into digital enterprises. Thinking about data as an asset requires organizations to change their mindsets, becoming more data-focused, and assembling and acquiring the tools and skills needed to manage data at speed and at scale.

New, Evolving Tools To Manage Big Data Will Grow At Double-Digit Rates

Artificial intelligence (AI) is back in vogue.

Big data becomes fast and approachable. (need for speed has fueled the adoption of faster
databases like Exasol and MemSQL, Hadoop-based stores like Kudu, and technologies that enable faster queries.)

Architectures mature to reject one-size-fits all frameworks.

Big data no longer just Hadoop. (Enterprises with complex, heterogeneous environments no longer want to adopt a siloed BI access point just for one data source (Hadoop). Answers to their questions are buried in a host of sources ranging from systems of record to cloud warehouses, to structured and unstructured data from both Hadoop and non-Hadoop sources.)

Point 2

Companies focus on business- driven applications to avoid data lakes from becoming swamps.

Organizations leverage data lakes from the get-go to drive value.(Organizations will demand repeatable and agile use of the lake for quicker answers.)

Point 3

Four Steps To A Data Management Strategy In Light Of Big Data

Data agility separates winners and losers. The emergence of agile processing models will enable the same instance of data to support batch analytics, interactive analytics, global messaging, database and file-based models.

Architectures mature to reject one-size-fits all frameworks

Point 4

The Cloudy Future of Hadoop

Intelligent networks lead to the rise of data clouds. As connections continue to evolve thanks to the Internet of Anything (IoAT) and machine-to-machine connectivity, silos of data will be replaced by clouds of data, Hortonworks says.

Convergence of IoT, cloud, and big data create new opportunities for self-service analytics.

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