Description
Improving Access to Data for Successful Business Intelligence
Improving Access to Data for
Successful Business Intelligence
Part 1: Meeting Today’s Business Requirements in an
Increasingly Complex Environment
Prepared for:
By Mike Ferguson
Intelligent Business Strategies
March 2014
W
H
I
T
E
P
A
P
E
R
INTELLIGENT
BUSINESS
STRATEGIES
Improving Access to Data for Successful Business Intelligence
Table of Contents
Introduction ............................................................................................................... 3
Today's Increasingly Complex Distributed Data Landscape ..................................... 4
The Agile BI Expectation .............................................................................. 4
Opposing Forces – Business Agility Versus Complexity of Data Access ...... 5
Business Requirements for Improved Information in a Modern Enterprise ............... 6
Improving the customer experience .............................................................. 6
Better risk management ................................................................................ 6
Streamline business operations .................................................................... 7
Develop new products and business models ................................................ 7
Conclusion ................................................................................................................ 8
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 2
Improving Access to Data for Successful Business Intelligence
INTRODUCTION
A key factor in successful business intelligence (BI) implementations is the
ability to easily access and integrate data. Several recent studies support
this, including an October 2013 survey
1
of more than four thousand C-suite
executives. The results show that customers are now rated as the most
influential people in the business, after the C-suite executives themselves.
It is not surprising therefore that access to information to improve customer
experience and to provide customer insight is now in high demand. In fact,
87% of Chief Marketing Officers (CMOs) view integration of cross-channel
touch point information and 83% view analytics to capture customer
insights as their most important initiatives over the next 3 to 5 years. 94% of
CMOs see advanced analytics as the most important technology to help
realise their goals around customer insights. Similarly Chief Financial
Officers (CFOs) cited the biggest gap (of 58%) where they need to do a
better job was in the ability to access and integrate information across the
enterprise. In addition, 84% of Chief Information Officers (CIOs) rated
Business Analytics and Optimization as their joint highest priority. The
results from a second survey
2
reinforce this and show that better access to
information is the single most important measure in making business
intelligence a success.
This series of three white papers titled “Improving Access to Data for
Successful Business Intelligence,” looks at the challenges that companies
are facing with their data, including:
• the increasing demand for more data from more sources to deepen
insight
• the business expectation to deliver BI quickly in an increasingly agile
way, irrespective of data complexity
In Part 2, we will also look at the business requirements driving demand for
deeper insights and at the changing analytical landscape, which now
consists of multiple analytical platforms beyond that of a just a data
warehouse. We will also look at the growth in adoption of self-service BI
tools in use in business areas and at key requirements for maintaining
good data access in an increasingly complex analytical environment. In
Part 3 we will look at how one vendor, Progress Software, is stepping up to
the challenge of simplifying access to data in order help organisations be
successful with their business intelligence initiatives.
1
The Customer-activated Enterprise – Insights from the Global C-Suite Study, IBM
Institute of Business Value, October 2013
2
Successful Business Intelligence 2
nd
Edition, Cindi Howson, Pg. 80 Fig 4.3
Better access to
information is the
single most
important measure
in making business
intelligence a
success
Companies are
becoming highly
customer focussed,
with analytics and
access to
information being
seen as strategically
important
C-suite executives
now regard
analytics and access
to information as
highest priority
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 3
Improving Access to Data for Successful Business Intelligence
TODAY’S INCREASINGLY COMPLEX DISTRIBUTED
DATA LANDSCAPE
In many companies the data landscape is becoming increasingly more
complex, with the number of data stores steadily growing. In the area of
transaction processing, it is still the case that multiple instances of
applications can exist across an organisation perhaps to support processes
and business functions in different geographies and different lines of
business. Perhaps the most notable change in transaction processing is
that decision that many organisations are beginning to run some of these
applications in the cloud, which of course means that corporate data now
exists both inside and outside the firewall.
In analytical environments, most companies have more than one data
warehouse today and are now introducing analytical relational database
appliances to support new analytical workloads. This is causing ‘islands’ of
overlapping data to exist across multiple analytical systems. In addition, big
data is now in the enterprise adding platforms such as Apache Hadoop and
NoSQL databases are also being incorporated into the data landscape.
Also, analytics is no longer about purely structured data. It is also about
unstructured data and with that comes demand for data from external
sources and marketplaces for specific types of big data analysis.
Within the enterprise, unstructured data is not only found in Hadoop; it also
exists in multiple places including enterprise content management systems,
email systems, CRM systems and in file stores right across the enterprise.
Looking at this evolution and increasingly complex setup, there is no doubt
that data is becoming more distributed. It exists inside and outside the
enterprise in many different systems, cloud providers, appliances and other
data stores. It also exists in many different formats. This increased
complexity makes it harder to know where data is located and how to
access it. Connectivity to data is becoming more complex and more critical
in an increasing distributed data landscape. Looking forward, this trend is
set to continue as more data sources continue to emerge. A good example
is the ‘internet of things’. Smart products and sensor networks will trigger a
tsunami of data and a quantum leap in the number of data sources that
businesses will need to access to stay competitive.
THE AGILE BI EXPECTATION
Despite the trend toward increasingly distributed data and more data
sources, there is an expectation from business that BI must be produced
and delivered in a more rapid and agile way than ever before. Business
organizations demand rapid development, along with flexibility to
accommodate change requests and to have those new requirements met
easily. The emergence of automated data warehouse development
software together with self-service BI tools has fuelled much of this
expectation. Agile data warehouse automation tools allow developers to
use metadata to automate the building of data warehousing systems by
generating physical data models, data cleansing and data integration jobs.
Self-service BI tools with in-memory data and data compression provide
The number of data
stores in most
organisations is
steadily growing
Transaction data
and customer data
now exist in the
cloud
Multiple data
warehouses and
analytical appliances
exist
Big data has brought
Hadoop and NoSQL
databases into the
enterprise
The data landscape
is becoming
increasingly complex
and data is
becoming more and
more distributed
Connectivity to data
is becoming critical
Distribution of data
will continue to
increase
Business
expectation is that BI
can be produced
quickly because of
new, more agile
tools
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 4
Improving Access to Data for Successful Business Intelligence
business users with the ability to rapidly interact with these tools changing
filters, dimensions measures and visualisations at the speed of thought.
OPPOSING FORCES – BUSINESS AGILITY VERSUS COMPLEXITY OF DATA
ACCESS
Increasingly distributed data in a variety of formats combined with the
demand for agile development means that when visualising data, business
users increasingly need access to multiple data sources—including data
inside the enterprise, data outside the enterprise in one or more clouds and
big data from a variety of sources.
Given that this is the case, what business requirements are driving the
need for business analysts to need to do this? Let’s take a look.
This expectation
exists despite the
fact that data
distribution is on the
increase
Business users
therefore need
access to multiple
data sources to
analyse and
visualise data
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 5
Improving Access to Data for Successful Business Intelligence
TODAY’S NEW BUSINESS REQUIREMENTS FOR
IMPROVED INFORMATION AND COMPETITIVE
ADVANTAGE
Since the recent global economic downturn, many C-level executives
around the world have responded to tough challenges by implementing
initiatives that transform their companies into leaner, more efficient and
more intelligent businesses.
To achieve this, several key requirements have emerged, including how to:
• Retain customers, their loyalty, and grow the customer base
• Manage and reduce risk
• Improve efficiency and effectiveness of operations
• Identify new products and business models
IMPROVE THE CUSTOMER EXPERIENCE
Today many companies are still organised around products or lines of
business as opposed to being organised around their customers. As a
result, customer data is highly distributed across many systems, including
product-oriented or line of business-oriented operational systems and data
warehouses. In addition, many companies have deployed Software as a
Service (SaaS)-based applications on the cloud such as Salesforce.com
where customer data may also reside. However, the demand to gain a 360-
degree understanding of customers has provided incentive for many
companies to evolve their approach and at the same time, seek access to
big data sources such as online clickstream data and social media data.
They also want to be able to view sequentially all inbound and outbound
interactions with customers to try to understand and improve the customer
experience across all channels. Quality of service is another high-priority
area. As a result, connectivity to all these sources becomes essential to
obtaining rich customer insight.
BETTER RISK MANAGEMENT
Risk management is another business requirement driving the need for
access to more data. For example, oil and gas companies are deploying
sensors to instrument oil and gas wells, pipelines and drilling equipment to
minimise risk to health and safety, the environment, and to avoid damage
their brand by preventing disasters. Banks want to manage credit risk of
their customers across all loan products and have risk-adjusted customer
relationship pricing. Insurance companies want to minimise risk of claims
from drivers by deploying “smart boxes” full of sensors in younger
customers’ vehicles to monitor how they drive to reduce claims and
improve loss ratios. Similarly, insurance companies that get all their
business from brokers now want to access and analyse unstructured text in
the broker documents that come into underwriters for them to make a
decision about whether to underwrite the risks. By doing this, they can pull
The need to retain
customers, reduce
risk, improve
operational
efficiency and create
new products are the
business drivers
creating the demand
for better information
The need for deeper
customer insight is
driving demand for
more customer data
from multiple data
sources
This includes data in
the cloud and new
big data sources
Access to big data is
also in demand to
help reduce risk
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 6
Improving Access to Data for Successful Business Intelligence
insights from the additional unstructured data that can be combined with
claims data to highlight new risk factors for use in risk models to improve
underwriting decisions and reduce the number of property claims. All of this
requires more data from multiple data sources.
STREAMLINE BUSINESS OPERATIONS
To reduce cost and improve efficiency, businesses must be able to monitor
and measure their end-to-end operations. For example, manufacturing
companies are deploying sensors in production lines to gain insight into
slow and costly activities in production. Logistics firms and retailers are
deploying sensors to monitor the flow of goods in supply and distribution
chains. Cities are using GPS sensors to monitor and optimise traffic flows.
To achieve these cost reductions and efficiency improvements mean that
big data must be combined with existing on-premise and cloud data, i.e.
structured and multi-structured data from multiple sources is now needed.
DEVELOP NEW PRODUCTS AND BUSINESS MODELS
The ability to add new data sources means that new insights are uncovered
that could easily show gaps in the market and provide opportunities to offer
new products and develop new business models, all leading to business
growth. For example, telecommunications firms could use GPS data and
data records to determine where people are located, where they have
come from, and what content they look at when attending specific events.
This information could lead to new products and services to offer customers
based on where they are. In addition, this kind of data could help create a
completely new business by selling GPS data to other organisations such
as retailers to conduct targeted flash advertising based on GPS location to
attract customers to buy a product or come into a store. Again it is the
combining of data from multiple data sources, both internal and external,
that empowers businesses to innovate in this manner.
These requirements clearly demonstrate that businesses now regard
deeper insight as strategically important to retaining customers, improving
customer experiences and driving overall growth. At the same time, more
data is needed to reduce risk and operational costs. More data is also
needed to open up new opportunity in the form of new products and
business models. All of this is about using data to drive better profit margins
and new business growth while reducing risk and remaining compliant with
regulations and legislation.
Sensor networks are
being deployed to
gain insight into
operations
This helps increase
speed of process
execution and
reduce cost
More data from
multiple data
sources is needed to
identify new markets
and the need for
new products
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 7
Improving Access to Data for Successful Business Intelligence
CONCLUSION
The increasingly complex data landscape, the demand for agile business
intelligence backed by new high-priority business drivers is driving the
demand for improved access to data from inside the enterprise, outside the
enterprise on the cloud, and from big data sources. As the number of data
sources continues to climb, data scientists, business analysts and decision
makers all want the ability quickly and easily access the data they need to
speed up the production of highly competitive actionable business insights
that drive better business and financial performance.
In Part 2 in this series, we will look at how these demands are changing the
analytical landscape, the growth in self-service BI tools, and the
requirements for improved data access in an analytical environment.
Improved access to data
is now needed to retain
and grow the customer
base
Access to multiple data
sources inside and
outside the enterprise is
also needed as data
becomes increasingly
more distributed
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 8
Improving Access to Data for Successful Business Intelligence
About Intelligent Business Strategies
Intelligent Business Strategies is a research and consulting company
whose goal is to help companies understand and exploit new developments
in business intelligence, analytical processing, data management and
enterprise business integration. Together, these technologies help an
organisation become an intelligent business.
Author
Mike Ferguson is Managing Director of Intelligent Business Strategies
Limited. As an analyst and consultant he specialises in business
intelligence and enterprise business integration. With over 32 years of IT
experience, Mike has consulted for dozens of companies on BI/Analytics,
big data, data governance, master data management and enterprise
architecture. He has spoken at events all over the world and written
numerous articles and blogs providing insights on the industry. Formerly he
was a principal and co-founder of Codd and Date Europe Limited – the
inventors of the Relational Model, a Chief Architect at Teradata on the
Teradata DBMS and European Managing Director of Database Associates,
an independent analyst organisation. He teaches popular master classes in
Big Data Analytics, New Technologies for Business Intelligence and Data
Warehousing, Enterprise Data Governance, Master Data Management, and
Enterprise Business Integration.
Water Lane, Wilmslow
Cheshire, SK9 5BG
England
Telephone: (+44)1625 520700
Internet URL: www.intelligentbusiness.biz
E-mail: [email protected]
Improving Access to Data for Successful Business Intelligence – Part 1
Copyright © 2014 by Intelligent Business Strategies
All rights reserved
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 9
doc_651675796.pdf
Improving Access to Data for Successful Business Intelligence
Improving Access to Data for
Successful Business Intelligence
Part 1: Meeting Today’s Business Requirements in an
Increasingly Complex Environment
Prepared for:
By Mike Ferguson
Intelligent Business Strategies
March 2014
W
H
I
T
E
P
A
P
E
R
INTELLIGENT
BUSINESS
STRATEGIES
Improving Access to Data for Successful Business Intelligence
Table of Contents
Introduction ............................................................................................................... 3
Today's Increasingly Complex Distributed Data Landscape ..................................... 4
The Agile BI Expectation .............................................................................. 4
Opposing Forces – Business Agility Versus Complexity of Data Access ...... 5
Business Requirements for Improved Information in a Modern Enterprise ............... 6
Improving the customer experience .............................................................. 6
Better risk management ................................................................................ 6
Streamline business operations .................................................................... 7
Develop new products and business models ................................................ 7
Conclusion ................................................................................................................ 8
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 2
Improving Access to Data for Successful Business Intelligence
INTRODUCTION
A key factor in successful business intelligence (BI) implementations is the
ability to easily access and integrate data. Several recent studies support
this, including an October 2013 survey
1
of more than four thousand C-suite
executives. The results show that customers are now rated as the most
influential people in the business, after the C-suite executives themselves.
It is not surprising therefore that access to information to improve customer
experience and to provide customer insight is now in high demand. In fact,
87% of Chief Marketing Officers (CMOs) view integration of cross-channel
touch point information and 83% view analytics to capture customer
insights as their most important initiatives over the next 3 to 5 years. 94% of
CMOs see advanced analytics as the most important technology to help
realise their goals around customer insights. Similarly Chief Financial
Officers (CFOs) cited the biggest gap (of 58%) where they need to do a
better job was in the ability to access and integrate information across the
enterprise. In addition, 84% of Chief Information Officers (CIOs) rated
Business Analytics and Optimization as their joint highest priority. The
results from a second survey
2
reinforce this and show that better access to
information is the single most important measure in making business
intelligence a success.
This series of three white papers titled “Improving Access to Data for
Successful Business Intelligence,” looks at the challenges that companies
are facing with their data, including:
• the increasing demand for more data from more sources to deepen
insight
• the business expectation to deliver BI quickly in an increasingly agile
way, irrespective of data complexity
In Part 2, we will also look at the business requirements driving demand for
deeper insights and at the changing analytical landscape, which now
consists of multiple analytical platforms beyond that of a just a data
warehouse. We will also look at the growth in adoption of self-service BI
tools in use in business areas and at key requirements for maintaining
good data access in an increasingly complex analytical environment. In
Part 3 we will look at how one vendor, Progress Software, is stepping up to
the challenge of simplifying access to data in order help organisations be
successful with their business intelligence initiatives.
1
The Customer-activated Enterprise – Insights from the Global C-Suite Study, IBM
Institute of Business Value, October 2013
2
Successful Business Intelligence 2
nd
Edition, Cindi Howson, Pg. 80 Fig 4.3
Better access to
information is the
single most
important measure
in making business
intelligence a
success
Companies are
becoming highly
customer focussed,
with analytics and
access to
information being
seen as strategically
important
C-suite executives
now regard
analytics and access
to information as
highest priority
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 3
Improving Access to Data for Successful Business Intelligence
TODAY’S INCREASINGLY COMPLEX DISTRIBUTED
DATA LANDSCAPE
In many companies the data landscape is becoming increasingly more
complex, with the number of data stores steadily growing. In the area of
transaction processing, it is still the case that multiple instances of
applications can exist across an organisation perhaps to support processes
and business functions in different geographies and different lines of
business. Perhaps the most notable change in transaction processing is
that decision that many organisations are beginning to run some of these
applications in the cloud, which of course means that corporate data now
exists both inside and outside the firewall.
In analytical environments, most companies have more than one data
warehouse today and are now introducing analytical relational database
appliances to support new analytical workloads. This is causing ‘islands’ of
overlapping data to exist across multiple analytical systems. In addition, big
data is now in the enterprise adding platforms such as Apache Hadoop and
NoSQL databases are also being incorporated into the data landscape.
Also, analytics is no longer about purely structured data. It is also about
unstructured data and with that comes demand for data from external
sources and marketplaces for specific types of big data analysis.
Within the enterprise, unstructured data is not only found in Hadoop; it also
exists in multiple places including enterprise content management systems,
email systems, CRM systems and in file stores right across the enterprise.
Looking at this evolution and increasingly complex setup, there is no doubt
that data is becoming more distributed. It exists inside and outside the
enterprise in many different systems, cloud providers, appliances and other
data stores. It also exists in many different formats. This increased
complexity makes it harder to know where data is located and how to
access it. Connectivity to data is becoming more complex and more critical
in an increasing distributed data landscape. Looking forward, this trend is
set to continue as more data sources continue to emerge. A good example
is the ‘internet of things’. Smart products and sensor networks will trigger a
tsunami of data and a quantum leap in the number of data sources that
businesses will need to access to stay competitive.
THE AGILE BI EXPECTATION
Despite the trend toward increasingly distributed data and more data
sources, there is an expectation from business that BI must be produced
and delivered in a more rapid and agile way than ever before. Business
organizations demand rapid development, along with flexibility to
accommodate change requests and to have those new requirements met
easily. The emergence of automated data warehouse development
software together with self-service BI tools has fuelled much of this
expectation. Agile data warehouse automation tools allow developers to
use metadata to automate the building of data warehousing systems by
generating physical data models, data cleansing and data integration jobs.
Self-service BI tools with in-memory data and data compression provide
The number of data
stores in most
organisations is
steadily growing
Transaction data
and customer data
now exist in the
cloud
Multiple data
warehouses and
analytical appliances
exist
Big data has brought
Hadoop and NoSQL
databases into the
enterprise
The data landscape
is becoming
increasingly complex
and data is
becoming more and
more distributed
Connectivity to data
is becoming critical
Distribution of data
will continue to
increase
Business
expectation is that BI
can be produced
quickly because of
new, more agile
tools
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 4
Improving Access to Data for Successful Business Intelligence
business users with the ability to rapidly interact with these tools changing
filters, dimensions measures and visualisations at the speed of thought.
OPPOSING FORCES – BUSINESS AGILITY VERSUS COMPLEXITY OF DATA
ACCESS
Increasingly distributed data in a variety of formats combined with the
demand for agile development means that when visualising data, business
users increasingly need access to multiple data sources—including data
inside the enterprise, data outside the enterprise in one or more clouds and
big data from a variety of sources.
Given that this is the case, what business requirements are driving the
need for business analysts to need to do this? Let’s take a look.
This expectation
exists despite the
fact that data
distribution is on the
increase
Business users
therefore need
access to multiple
data sources to
analyse and
visualise data
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 5
Improving Access to Data for Successful Business Intelligence
TODAY’S NEW BUSINESS REQUIREMENTS FOR
IMPROVED INFORMATION AND COMPETITIVE
ADVANTAGE
Since the recent global economic downturn, many C-level executives
around the world have responded to tough challenges by implementing
initiatives that transform their companies into leaner, more efficient and
more intelligent businesses.
To achieve this, several key requirements have emerged, including how to:
• Retain customers, their loyalty, and grow the customer base
• Manage and reduce risk
• Improve efficiency and effectiveness of operations
• Identify new products and business models
IMPROVE THE CUSTOMER EXPERIENCE
Today many companies are still organised around products or lines of
business as opposed to being organised around their customers. As a
result, customer data is highly distributed across many systems, including
product-oriented or line of business-oriented operational systems and data
warehouses. In addition, many companies have deployed Software as a
Service (SaaS)-based applications on the cloud such as Salesforce.com
where customer data may also reside. However, the demand to gain a 360-
degree understanding of customers has provided incentive for many
companies to evolve their approach and at the same time, seek access to
big data sources such as online clickstream data and social media data.
They also want to be able to view sequentially all inbound and outbound
interactions with customers to try to understand and improve the customer
experience across all channels. Quality of service is another high-priority
area. As a result, connectivity to all these sources becomes essential to
obtaining rich customer insight.
BETTER RISK MANAGEMENT
Risk management is another business requirement driving the need for
access to more data. For example, oil and gas companies are deploying
sensors to instrument oil and gas wells, pipelines and drilling equipment to
minimise risk to health and safety, the environment, and to avoid damage
their brand by preventing disasters. Banks want to manage credit risk of
their customers across all loan products and have risk-adjusted customer
relationship pricing. Insurance companies want to minimise risk of claims
from drivers by deploying “smart boxes” full of sensors in younger
customers’ vehicles to monitor how they drive to reduce claims and
improve loss ratios. Similarly, insurance companies that get all their
business from brokers now want to access and analyse unstructured text in
the broker documents that come into underwriters for them to make a
decision about whether to underwrite the risks. By doing this, they can pull
The need to retain
customers, reduce
risk, improve
operational
efficiency and create
new products are the
business drivers
creating the demand
for better information
The need for deeper
customer insight is
driving demand for
more customer data
from multiple data
sources
This includes data in
the cloud and new
big data sources
Access to big data is
also in demand to
help reduce risk
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 6
Improving Access to Data for Successful Business Intelligence
insights from the additional unstructured data that can be combined with
claims data to highlight new risk factors for use in risk models to improve
underwriting decisions and reduce the number of property claims. All of this
requires more data from multiple data sources.
STREAMLINE BUSINESS OPERATIONS
To reduce cost and improve efficiency, businesses must be able to monitor
and measure their end-to-end operations. For example, manufacturing
companies are deploying sensors in production lines to gain insight into
slow and costly activities in production. Logistics firms and retailers are
deploying sensors to monitor the flow of goods in supply and distribution
chains. Cities are using GPS sensors to monitor and optimise traffic flows.
To achieve these cost reductions and efficiency improvements mean that
big data must be combined with existing on-premise and cloud data, i.e.
structured and multi-structured data from multiple sources is now needed.
DEVELOP NEW PRODUCTS AND BUSINESS MODELS
The ability to add new data sources means that new insights are uncovered
that could easily show gaps in the market and provide opportunities to offer
new products and develop new business models, all leading to business
growth. For example, telecommunications firms could use GPS data and
data records to determine where people are located, where they have
come from, and what content they look at when attending specific events.
This information could lead to new products and services to offer customers
based on where they are. In addition, this kind of data could help create a
completely new business by selling GPS data to other organisations such
as retailers to conduct targeted flash advertising based on GPS location to
attract customers to buy a product or come into a store. Again it is the
combining of data from multiple data sources, both internal and external,
that empowers businesses to innovate in this manner.
These requirements clearly demonstrate that businesses now regard
deeper insight as strategically important to retaining customers, improving
customer experiences and driving overall growth. At the same time, more
data is needed to reduce risk and operational costs. More data is also
needed to open up new opportunity in the form of new products and
business models. All of this is about using data to drive better profit margins
and new business growth while reducing risk and remaining compliant with
regulations and legislation.
Sensor networks are
being deployed to
gain insight into
operations
This helps increase
speed of process
execution and
reduce cost
More data from
multiple data
sources is needed to
identify new markets
and the need for
new products
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 7
Improving Access to Data for Successful Business Intelligence
CONCLUSION
The increasingly complex data landscape, the demand for agile business
intelligence backed by new high-priority business drivers is driving the
demand for improved access to data from inside the enterprise, outside the
enterprise on the cloud, and from big data sources. As the number of data
sources continues to climb, data scientists, business analysts and decision
makers all want the ability quickly and easily access the data they need to
speed up the production of highly competitive actionable business insights
that drive better business and financial performance.
In Part 2 in this series, we will look at how these demands are changing the
analytical landscape, the growth in self-service BI tools, and the
requirements for improved data access in an analytical environment.
Improved access to data
is now needed to retain
and grow the customer
base
Access to multiple data
sources inside and
outside the enterprise is
also needed as data
becomes increasingly
more distributed
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 8
Improving Access to Data for Successful Business Intelligence
About Intelligent Business Strategies
Intelligent Business Strategies is a research and consulting company
whose goal is to help companies understand and exploit new developments
in business intelligence, analytical processing, data management and
enterprise business integration. Together, these technologies help an
organisation become an intelligent business.
Author
Mike Ferguson is Managing Director of Intelligent Business Strategies
Limited. As an analyst and consultant he specialises in business
intelligence and enterprise business integration. With over 32 years of IT
experience, Mike has consulted for dozens of companies on BI/Analytics,
big data, data governance, master data management and enterprise
architecture. He has spoken at events all over the world and written
numerous articles and blogs providing insights on the industry. Formerly he
was a principal and co-founder of Codd and Date Europe Limited – the
inventors of the Relational Model, a Chief Architect at Teradata on the
Teradata DBMS and European Managing Director of Database Associates,
an independent analyst organisation. He teaches popular master classes in
Big Data Analytics, New Technologies for Business Intelligence and Data
Warehousing, Enterprise Data Governance, Master Data Management, and
Enterprise Business Integration.
Water Lane, Wilmslow
Cheshire, SK9 5BG
England
Telephone: (+44)1625 520700
Internet URL: www.intelligentbusiness.biz
E-mail: [email protected]
Improving Access to Data for Successful Business Intelligence – Part 1
Copyright © 2014 by Intelligent Business Strategies
All rights reserved
Copyright ©Intelligent Business Strategies Limited, 2014, All Rights Reserved 9
doc_651675796.pdf