Business Intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all of the factors that affect your business. It is imperative that you have an in depth knowledge about factors such as your customers, competitors, business partners, economic environment, and internal operations to make effective and good quality business decisions. Business intelligence enables you to make these kinds of decisions.
Get your complimentary copy of Gartner’s report for in-depth analysis of where BI is headed in 2016, who the major vendors are, and why Qlik is positioned in the Leaders quadrant for the sixth consecutive year.
When comparing the architecture for Ceph and SolidFire, it is clear
that both are scale-out storage systems designed to use commodity
hardware, and the strengths of each make them complementary
solutions for datacenter design.
Founded in 1992 as a provider of integrated network, voice and data centre solutions, Colt’s business today has grown to encompass a wide range of IT services, spanning enterprise application hosting, business critical cloud and end-user computing solutions. Colt has 29 data centre locations supporting thousands of customers across 28 countries in Europe and Asia, including Swiss International Airlines, Shurgard, Berenberg, and Jaguar Land Rover. Colt’s award-winning solution portfolio is based on end-to-end data centre, network and IT services capabilities; its aim is to help its customers compete and win in their markets without being held back by hardware, licensing and resource limitations.
Quality of service (QoS) is a critical enabling technology for enterprises and service providers wanting to deliver consistent primary storage performance to business-critical applications in a multi-tenant or enterprise infrastructure. The type of applications that require primary storage services typically demand greater levels of performance than what is readily available from traditional storage infrastructures today. However, simply providing raw performance is often not the only objective in these use cases. For a broad range of business-critical applications, consistent and predictable performance are the more important metrics. Unfortunately, neither is easily achievable within traditional storage arrays.
When the right approach is applied, analytics can drive more effective marketing strategies. While marketers understand the role analytics plays within the organization, most are not leveraging analytics to really drive enterprise performance. We surveyed 100+ business leaders to understand the state of analytics maturity across today’s leading organizations, uncovering common challenges teams are facing in their quest to use data and analytics to deliver a competitive advantage.
What We Uncovered:
- 73% of analytic professionals claim to work for an analytically-driven company
- Only 42% of companies have a strategy for using analytics across the enterprise
- Just 38% of companies share results of their analytic insights outside their department
- 81% of organizations rely on 3rd parties for at least some portion of their analysis
Download the report to learn how marketers, like yourself, view themselves in light of using analytics to drive their business.
New Enterprise challenge has emerged. With the number of APIs growing rapidly, managing them one-off or via Excel or corporate wiki is no longer feasible.
The smartest organizations have discovered a set of best practices to design powerful APIs that leverage existing services, to effectively manage those APIs throughout their lifecycle and to scale their deployment across consumers and devices. This eBook examines the relationship between APIs and services and presents the key elements of a successful API strategy in the form of 7 habits.
In this eBook you will learn:
- How to leverage existing services in the API economy
- Where to get started with your API strategy
- Key criteria for selecting an API Management solution
- Strategies to overcome API security and identity challenges
- How and why to apply the fundamentals of API First Design
Every corner of an enterprise needs technology to build new applications for their specific function or customer. IT needs to transform from its traditional function as the sole technology provider to become an adaptive, responsive and nimble organization that can keep up with the pace of the digital era as well as embrace the opportunities provided by a change-driven environment. This transformation can occur only if IT transforms itself into a strategic business enabler rather than a centralized technology function.
Being an enabler means that IT has to decentralize and democratize application development and data access to the different Lines of Business (LoBs) and functional business partners. This way, IT can concentrate on a partnership with the business - i.e. providing a set of strategic and consistent assets and technology.
Today’s successful organization needs to be able to turn on a dime, changing its product or service direction as fast as its customers’ needs require. The successful business of the 21st century crosses all boundaries; can quickly meet and adapt to competition, whether it comes from another part of the world, another industry or a startup; or it can use its core competencies to extend itself in new ways. Welcome to the Composable Enterprise. This kind of company—powered by cloud, open APIs, data analytics, mobile and social, and connected to the Internet of Things—is redefining markets and raising consumer expectations. The composable enterprise casts away the hierarchical and hardwired systems and processes that defined its predecessors, and represents a radical rethinking of how
technology can serve innovation and how innovation can serve customers.
In every industry today, businesses feel a fierce urgency to become customer-centric. They want to know what they can do to preserve and expand existing customer relationships and attract the best new customers.
Analytics is more important to success than ever before, and it’s a business practice that has momentum. Fifty-eight percent of the respondents in a recent survey published in the MIT Sloan Management Review stated that the use of analytics gave their companies a competitive advantage, up from 37 percent the prior year. Enterprise-scale companies report dramatic successes with analytics.
This EMA case study profiles the implementation of the Snowflake Elastic Data Warehouse, a new generation of cloud-based data warehouses, by Accordant Media. This document details significant tangible and intangible improvements and opportunities the Snowflake solution created for the Accordant Media infrastructure and analytical teams.
For an increasing number of organizations, enterprise performance management (EPM) tools are enabling senior finance executives to integrate plans, understand where they're losing money, move from annual budgets to rolling forecasts, and identify opportunities for strategic improvements. During this Webcast, a panel of experts will explore: • Why business intelligence and business analytics are each important to your business; • How Big Data and analytics can help your organization answer more questions and ask even better ones; • The capabilities that enterprise performance management software offers organizations; and • How to evaluate what your organization can gain by implementing enterprise performance management software.
The Pivot3 N5 storage architecture was designed from the ground up to maximize the business value of data for customers. Our storage team recognized that with flash becoming pervasive in the datacenter, a new storage architecture was needed to help users manage workload performance. With other architectures, painstaking planning is required to prioritize data into specific categories for performance, availability, reliability, backup, etc., and then even more effort is spent designing and implementing storage systems that can meet those goals.
We designed a storage architecture that makes it simple for customers to prioritize their data, and let the storage system take care of managing the data to meet those prioritizations.
VCE VxRail Appliances enable organizations to create IT certainty by eliminating complexity and collapsing cost structures while leveraging their existing VMware investments. Based on VMware’s VMware's market-leading Hyper-Converged Software, VxRail delivers a known and proven building block for the software defined data center. It provides IT organizations with a full range of options to create a flexible, optimized infrastructure that dramatically simplifies their IT operations while reducing costs.
Managing your device keeps getting more complex and your admins are juggling more complicated security and management tasks than ever before. Until now, you have needed many complex and disparate tools to secure and manage your devices. But now Windows 10 and MobileIron make your life much simpler by streaming many traditional PC management responsibilities.
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.
Is your data architecture up to the challenge of the big data era? Can it manage workload demands, handle hybrid cloud environments and keep up with performance requirements? Here are six reasons why changing your database can help you take advantage of data and analytics innovations.
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.