apt

Will the “programmable era” of computers be replaced by Cognitive Computing systems which can learn from interactions and reason through dynamic experience just like humans? With rapidly increasing volumes of Big Data, there is a compelling need for smarter machines to organize data faster, make better sense of it, discover insights, then learn, adapt, and improve over time without direct programming. This paper is sponsored by: Cognitive Scale.

Acting Quickly – Or Not at All The pace of business is accelerating. Enterprises must do more things, do them more quickly – and then adjust to market and competitive forces and do them differently. They must adapt in order to remain differentiated, and with that differentiation, hopefully build and sustain competitive advantage.

Interactive applications have changed dramatically over the last 15 years. In the late ‘90s, large web companies emerged with dramatic increases in scale on many dimensions: · The number of concurrent users skyrocketed as applications increasingly became accessible · via the web (and later on mobile devices). · The amount of data collected and processed soared as it became easier and increasingly · valuable to capture all kinds of data. · The amount of unstructured or semi-structured data exploded and its use became integral · to the value and richness of applications. Dealing with these issues was more and more difficult using relational database technology. The key reason is that relational databases are essentially architected to run a single machine and use a rigid, schema-based approach to modeling data. Google, Amazon, Facebook, and LinkedIn were among the first companies to discover the serious limitations of relational database technology for supporting these new application requirements. Commercial alternatives didn’t exist, so they invented new data management approaches themselves. Their pioneering work generated tremendous interest because a growing number of companies faced similar problems. Open source NoSQL database projects formed to leverage the work of the pioneers, and commercial companies associated with these projects soon followed. Today, the use of NoSQL technology is rising rapidly among Internet companies and the enterprise. It’s increasingly considered a viable alternative to relational databases, especially as more organizations recognize that operating at scale is more effectively achieved running on clusters of standard, commodity servers, and a schema-less data model is often a better approach for handling the variety and type of data most often captured and processed today.

Enterprise metadata management and data quality management are two important pillars of successful enterprise data management for any organization. A well implemented enterprise metadata management platform can enable a successful data quality management at the enterprise level. This paper describes in detail an approach to integrate data quality and metadata management leveraging the Adaptive Metadata Manager platform. It explains the various levels of integrations and the benefits associated with each.

Everything about data has changed, but that only means that data models are even more essential to understanding that data so that businesses can know what it means. As development methodologies change to incorporate Agile workflows, data architects must adapt to ensure models stay relevant and accurate. This whitepaper describes key requirements for Agile data modeling and shows how ER/Studio supports this methodology.

Data governance is a lifecycle-centric asset management activity. To understand and realize the value of data assets, it is necessary to capture information about them (their metadata) in the connected way. Capturing the meaning and context of diverse enterprise data in connection to all assets in the enterprise ecosystem is foundational to effective data governance. Therefore, a data governance environment must represent assets and their role in the enterprise using an open, extensible and “smart” approach. Knowledge graphs are the most viable and powerful way to do this. This short paper outlines how knowledge graphs are flexible, evolvable, semantic and intelligent. It is these characteristics that enable them to: • capture the description of data as an interconnected set of information that meaningfully bridges enterprise metadata silos. • deliver integrated data governance by addressing all three aspects of data governance — Executive Governance, Representative Governance, and App

With future business intelligence solutions clearly evolving from data that comes from highly efficient and well behaved systems, to data that comes from the extended enterprise where data is not necessarily so well structured and behaved - Organizations are forced into a more collaborative mode of operation with their core infrastructure being adapted from the consumer space, and to the extent possible, conformed to their existing repositories. This whitepaper attempts to address various challenges consumers face while managing enormous data sets within the context of this complex scenario. Further, we’ll try to answer the question: Is Big Data Governance really that different from traditional data governance initiatives? Finally, we’ll see how AnalytiX™ Mapping Manager™ can help organizations accelerate the development and deployment of a successful Big Data/ Business Intelligence platform and accelerate delivery of all sorts of data – structured, semi-structured as well as unstruc

AnalytiX DS Mapping Manager is an award winning platform that has enabled organizations worldwide to meet challenges, bring wide-spread collaboration, and put structure and governance in place, regardless of the size of their architecture, data, or user base. Scalable, adaptable, and value-added through its feature rich modules, it can make a difference as to whether you see BASEL III as a challenge or an opportunity.

Establishing context and knowledge capture In today’s knowledge-infused world, it is vitally important for organizations of any size to deploy an intuitive knowledge platform that enables delivery of the right information at the right time, in a way that is useful and helpful. Semantic technology processes content for meaning, allowing for the ability to understand words in context: it allows for better content processing and interpretation, therefore enabling content organization and navigation, which in turn increases findability.

Big Data is the future of business. According to CloudTweaks.com, as much as 2.5 quintillion bytes of data are produced each day, with most of this data being captured by Big Data. With its ability to transfer all data sources all into one centralized place, Big Data provides opportunities, clearer visions, customer conversations and transactions. However, with the dazzling big promise of Big Data comes a potentially huge letdown. If this vast pool of information resources is not accessible or usable, it becomes useless. This paper examines strategies for building the most value into your Big Data system by enabling process controls to effectively mine, access and secure Big Data.

In today’s digital business world, accurate address and geolocation data is invaluable. But, address capture is something that is often overlooked from a user and business perspective. Clean address capture can enhance user experience, not only while entering an address, but also during the entire customer journey. Download this eBook to learn how global address validation tools can help: • Simplify address capture on web-based forms • Accurately pinpoint customer locations • Improve efficiencies in shipping and logistics • Define sales and marketing territories and enrich address information

Enterprises are focusing on becoming ever more data-driven, meaning that it is simply unacceptable to allow data to go to waste. Yet, as the amount of data businesses collect and control continues to increase exponentially, many organizations are failing to derive enough business value from their data. Companies are feeling the pressure to extract maximum value from all of their data, both defensive and offensive. Defensive analytics are the “plumbing aspects” of data management that must be captured to mitigate risk and establish a basic understanding of business performance. Offensive analytics build on defensive analytics and support overarching business objectives, strategic initiatives and long-term goals using predictive models. In this whitepaper, you will learn how to address many challenges, including streamlining operational reporting, delivering insight and providing a single, unified platform for everyone.

Change data capture (CDC) technology can modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems. To realize these benefits, enterprises need to understand how this critical technology works, why it’s needed, and what their Fortune 500 peers have learned from their CDC implementations. This book serves as a practical guide for enterprise architects, data managers and CIOs as they enable modern data lake, streaming and cloud architectures with CDC. Read this book to understand: ? The rise of data lake, streaming and cloud platforms ? How CDC works and enables these architectures ? Case studies of leading-edge enterprises ? Planning and implementation approaches

This Dive Deep analyst report looks at the process of building an environment for what can be aptly termed Agile Business Analytics.

Data Governance and Metadata Management are two closely associated Data Management Capabilities which organizations must address in order to truly turn their data into Information Assets.

Everything about data has changed, but that only means that data models are even more essential to understanding that data so that businesses can know what it means. As development methodologies change to incorporate Agile workflows, data architects must adapt to ensure models stay relevant and accurate. This whitepaper describes key requirements for Agile data modeling and shows how ER/Studio supports this methodology.

Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: What data virtualization is and its benefits When and when not to use data virtualization How to deploy data virtualization to benefit your business How to unlock the value of your SAP data

Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. TIBCO® Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: •?What data virtualization is and its benefits •?When and when not to use data virtualization •?How to deploy data virtualization to benefit your business

Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: •? What data virtualization is and its benefits •? When and when not to use data virtualization •? How to deploy data virtualization to benefit your business •? How to unlock the value of your SAP data

Over the past decade, businesses have made tremendous investments in information capture, storage, and analysis. But having a wealth of data isn’t the same as having valuable information. TIBCO® Data Virtualization products and services provide a way to turn your data stores into valuable information that improves decision-making and propels experimentation and innovation. This paper explains: •? What data virtualization is and its benefits •? When and when not to use data virtualization •? How to deploy data virtualization to benefit your business

Enterprises must continuously change to keep ahead of the competition, reduce silos, improve connectivity and respond rapidly to a changing world. Organisations also need to drive continuous innovation with technology that helps them adapt faster. So if you’re thinking of replacing your legacy ERP system, start by asking yourself these three essential questions:

Certaines dynamiques d’entreprise sont particulièrement bien adaptées à des solutions de communication dans le cloud.

Intapp Time provides superior business intelligence thatchangesyour firm’sfundamental relationship with time.Thisunified suite of applications gives timekeepers access to time data and capture wherever they are: in the office, on a mobile device, online and offline.It is user-centric, offering a completely automated option while fullysupporting hands-on tracking—contemporaneous or reconstructionist.Intapp Time helps your business mine time data to reveal new sources of revenue, inform staff decisions, increase project efficiency, and reduce time leakage.

DELL DOCKS — GIVING YOU MORE POWER TO GET AHEAD. Designed to efficiently connect to displays, keyboards, mice, printers, networks and other accessories, Dell docks expand your laptop, mobile workstation or 2-in-1 capabilities so you can quickly connect to all your devices at your desk.

For 25 years, OptiPlex has continuously adapted to the new ways you work. The next generation of innovative form factors and versatile accessories unleash your workforce potential like never before