Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on-premises data with new third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements.
To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
Data is the lifeblood of business. And in the era of digital business,
the organizations that utilize data most effectively are also the most
successful. Whether structured, unstructured or semi-structured,
rapidly increasing data quantities must be brought into organizations,
stored and put to work to enable business strategies. Data integration
tools play a critical role in extracting data from a variety of sources and
making it available for enterprise applications, business intelligence
(BI), machine learning (ML) and other purposes. Many organization
seek to enhance the value of data for line-of-business managers by
enabling self-service access. This is increasingly important as large
volumes of unstructured data from Internet-of-Things (IOT) devices
are presenting organizations with opportunities for game-changing
insights from big data analytics. A new survey of 369 IT professionals,
from managers to directors and VPs of IT, by BizTechInsights on
behalf of IBM reveals the challe
As the information age matures, data has become the most
powerful resource enterprises have at their disposal. Businesses
have embraced digital transformation, often staking their
reputations on insights extracted from collected data. While
decision-makers hone in on hot topics like AI and the potential of
data to drive businesses into the future, many underestimate the
pitfalls of poor data governance. If business decision-makers can’t
trust the data within their organization, how can stakeholders and
customers know they are in good hands? Information that is not
correctly distributed, or abandoned within an IT silo, can prove
harmful to the integrity of business decisions.
Connected Intelligence in Insurance
Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI).
Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever.
What you will learn:
The insurance industry's global digital trends, supported by data and analysis
What capabilities will make the insurers of the future become disruptors in their industry
Notable leaders based on IDC Financial Insights research and their respective use cases
Essential guidance from IDC
As recognized leader in master data management (MDM), and a pioneer in data asset management, TIBCO EBX™ software is an innovative, single solution for managing, governing, and consuming all your shared data assets. It includes all the enterprise class capabilities you need to create data management applications including user interfaces for authoring and data stewardship, workflow, hierarchy management, and data integration tools. And it provides an accurate, trusted view of business functions, insights, and decisions to empower better decisions and faster, smarter actions.
Download this datasheet to learn:
What makes EBX™ software unique
Various capabilities of EBX software
The data it manages
Published By: Teradata
Published Date: Jun 12, 2013
Health plans and insurers know that to thrive over the next 3-5 years, they must dramatically improve their ability to engage with individual consumers.
The combination of Teradata products; an integrated data warehouse, Aster big data analytics and Aprimo integrated communication management, creates actionable analytic capabilities unparalleled in its ability to help companies achieve these goals. this white paper details how health plans and insurers can use Teradata to succeed in today’s healthcare environment.
An analytics revolution is upon us. Knowledge workers are in short supply, the competition for talent has gone global; turnover is rising; and employee engagement is stagnant at best. How can companies attract, retain, and develop employees who can drive business results and have the data to back up these decisions? A recent survey found more than 80% of respondents said that they needed talent-related insights to make business decisions. Yet most enterprises still base talent decisions on gut feeling. Few can offer analytic evidence to support their hunches. Now, finally, analytics are beginning to drive decisions about people.
Until recently, ConAgra Foods struggled to collect accurate, analyzable data about its workforce. Information was spread across the organization in siloed systems within various departments and was often difficult to reconcile. In a few short years, however, ConAgra Foods has been able to leverage technology solutions to gain real-time insights into its employee data and can now analyze its workforce across a wide range of subject areas. Download this case study to see how ConAgra Foods transformed the role of HR through analytics, and to get guidance on how your organization can adopt a similar approach.
Published By: MarkLogic
Published Date: Mar 13, 2015
Big Data has been in the spotlight recently, as businesses seek to leverage their untapped information resources and win big on the promise of big data. However, the problem with big data initiatives are that organizations try using existing information management practices and legacy relational database technologies, which often collapse under the sheer weight of the data. In this paper, MarkLogic explains how a new approach is needed to handle the volume, velocity, and variety of big data because the current relational model that has been the status quo is not working. Learn about the NoSQL paradigm shift, and why NoSQL is gaining significant market traction because it solves the fundamental challenges of big data, achieving better performance, scalability, and flexibility. Learn how MarkLogic’s customers are reimagining their data to:
- Make the world more secure
- Provide access to valuable information
- Create new revenue streams
- Gain insights to increase market share
- Reduce b
Business users want the power of analytics—but analytics can only be as good as the data. To perform data discovery and exploration, use analytics to define desired business outcomes, and derive insights to help attain those outcomes, users need good, relevant data. Executives, managers, and other professionals are reaching for self-service technologies so they can be less reliant on IT and move into advanced analytics formerly limited to data scientists and statisticians. However, the biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation.
Retail is a data-intensive industry. Knowing the customer better than competition and having the ability to orchestrate business decisions is the new retail competitive battlefield. Read the white paper to learn customer insights on the future of retail analytics.
In our 33-criteria evaluation of customer analytics vendors, we identified the 11 most significant software providers in this category - adobe, agilone, alteryx, angoss, FICo, IBM, Manthan, Pitney Bowes, saP, sas, and teradata - and researched, analyzed, and scored them. this evaluation details our findings about how well each vendor fulfills our criteria and where each vendor stands in relation to each other. this report will help customer insights (CI) professionals and marketers make the right choice for their customer analytics needs.
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
Ordinary analytics tools can’t keep up with today’s digital, multichannel and demanding customers. This guide highlights three major challenges associated with traditional analytics and how innovative strategies combined with IBM’s Customer Experience Analytics solution can solve them.
In this webinar, you will learn:
- How to create a safe environment for honest feedback so it’s an invitation, not an imposition
- Best practices for collecting feedback, from unstructured conversations to regular pulse surveys
- What to do with the data you’ve collected, and how to use insights to create action plans that result in happier employees and better business performance
Published By: Veritas
Published Date: May 12, 2016
The Data Genomics Index is a first-of-its-kind benchmark analysis of data stored within a typical enterprise environment. This report reveals insights into data growth, data age, and data type thereby providing organizations with the comparison standard for beginning to take action on their data.
In addition to the Index, Veritas has founded the Data Genomics Project. This community of likeminded data scientists, industry experts and thought leaders will come together to surface the true nature of enterprise environments, build the data-genome that matters for information management, and share the discussion with a world struggling to solve tremendous data growth challenges.
What do these market-defining trends have in common?
· Analytics for all
· Analytics as competitive differentiator
· Internet of Things
· Artificial intelligence/Machine learning/Cognitive computing
· Real-time analytics/event management
They all rely on data – timely, accurate data delivered within an insightful context – to deliver value.
The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and
values of the data-driven enterprise?
It’s going to take a special type of professional to deliver that value to enterprises. Organizations are
seeking professionals to step forward and take the lead, provide guidance and lend expertise to move
into the brave new world of digital. The move to digital and all that it entails – sophisticated data
analytics, online customer engagement and digital process efficiency – requires, above all, the skills
and knowledge associated with handling data and turning it into insights. The move to digital is also a
Published By: Genesys
Published Date: Feb 21, 2018
Routing is a fundamental component of your customer experience strategy. True omnichannel routing breaks down channel silos and gathers intelligence upfront through context and data to deliver the personalized, seamless engagement your customers now expect.
Learn how you can move beyond single interactions with true omnichannel routing:
• Dynamically match customers from any touchpoint, over any channel, to the agent with the optimal insights, skill set and proficiency
• Enable seamless transitions between digital self-service and live employee contact
• Replace single, random interactions with thoughtfully designed and optimized customer journeys
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
Data governance is all about managing data, by revising that data to standardize it and
bring consistency to the way it is used across numerous business initiatives. What’s
more, data governance ensures that critical data is available at the right time to the
right person, in a standardized and reliable form. A benefit that fuels better organization
of business operations, resulting in improved productivity and efficiency of that
organization. Thus, the importance of proper data governance cannot be understated.
The concepts of data governance have evolved, where the first iteration of data
governance, often referred to as version 1.0, focused on three simplistic elements:
objectives, structure and processes; having a limited focus and scope due to its
tactical usage. The opportunity from the growing value of data in the realm of
analytics, business intelligence, and generating insights was left unrealized. Today,
organizations are moving towards what can be called Data Governance 2.0,
Every day, torrents of data inundate IT organizations and overwhelm
the business managers who must sift through it all to
glean insights that help them grow revenues and optimize
profits. Yet, after investing hundreds of millions of dollars into
new enterprise resource planning (ERP), customer relationship
management (CRM), master data management systems (MDM),
business intelligence (BI) data warehousing systems or big data
environments, many companies are still plagued with disconnected,
“dysfunctional” data—a massive, expensive sprawl of
disparate silos and unconnected, redundant systems that fail to
deliver the desired single view of the business.
To meet the business imperative for enterprise integration and
stay competitive, companies must manage the increasing variety,
volume and velocity of new data pouring into their systems from
an ever-expanding number of sources. They need to bring all
their corporate data together, deliver it to end users as quickly as
possible to maximize
The Smarter Process platform is IBM’s solution for reinventing
business operations in a way that infuses every process
with intelligence and expertise to deliver greater customer
centricity, which in turn fuels top-line growth. It incorporates
Business Process Management, Case Management,
Operational Decision Management and Process Analytics,
along with Process Discovery and Design with an objective of
ensuring that customers find it easy to do business and that
every interaction includes positive touch points.
Within the context of this new imperative, accessing cloud
efficiencies, leveraging mobile for greater engagement,
mining big data for insights, and enhancing customer
relationships via social media, are proving to be critical and
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