capture data

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.

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

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.

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

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

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.

Metadata Management is the process of ensuring that all metadata associated with a digital asset is captured, organized, stored and made available for use by and within other applications. Metadata Management begins at the moment the digital asset is created by an application or captured by digital imaging.

With 50 to 100 billion things expected to be connected to the Internet by 2020, we are now experiencing a major paradigm shift that is revolutionizing business. More and more of the objects we use every day—including those in our factories, utilities, and railroads—are used to capture and distribute information that is helping us know more and do more. The TechWiseTV team and guest experts take an in-depth look at how industries like these are utilizing the data they are gathering from the factory floor all the way out to the field. This exploration into how the Internet of Things actually works in the real world and what your organization must do to take full advantage of it is a great opportunity to understand the practical challenges and specific technology involved in bringing all this potential to life.

This RSR custom research report explores the impact of omnichannel methods on merchandising, marketing and the supply chain; specifically, what analytical capabilities address the challenges that omnichannel selling and fulfillment pose for retailers. Consumers today routinely begin their shopping journeys online, but complete their purchases in nearby stores, in their “home” stores or delivered directly to their doors. Retail analytics enables organizations to capture data from their customers' journeys. Retailers that successfully deliver relevant omnichannel experiences while gaining a more sophisticated understanding of demand (where and how it is initiated) will enhance their brands’ value and create compelling and profitable customer relationships.

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better

Looking to drive up billing accuracy? The time, expense, and mileage data you capture from your people is vital. The top five percent of professional services organizations (PSOs) achieve top financial results by making money on every facet of the business; earning higher margins and revenue for every employee, project, and consultant than their rivals. Download this finance-focused eGuide to find out how the best PSOs harness that key data – and get a cheat sheet on how to outdo your competition.

Download this whitepaper to learn more about how to capture, analyze and manage a tidal wave of structured and unstructured data, turn this data into operational intelligence, And how to overcome the limitations of databases and data management tools that weren’t designed for a world of big data with Dell.

While the inevitable move to Windows 7 has been on the horizon for IT departments for several years, it’s clear that migration projects continue to plague many IT professionals. RES Software commissioned its second Windows 7 migration survey in June 2012 to assess the progress of these implementations in relation to a previous benchmarking survey issued in 2010. The most recent survey captures data from more than 330 IT professionals in North America and Europe across multiple industries and job functions. The results have been analysed and are highlighted within this research brief.

Act now to gain important insight on the three key drivers for best-in-class Accounts Payable departments

The supply chain generates huge volumes of data captured in ERP, CRM, demand planning and other systems. Download this whitepaper to learn how FusionOps Machine Learning can provide companies with a more accurate, granular understanding of their business by harmonizing these disparate data sources in the cloud, and applying machine learning algorithms.

To have the greatest impact within your company, you need to contribute to strategy rather than focusing on tactical issues. But, to accomplish this means that you have to tap into your company's financial performance and unearth insights that will help senior leaders make better decisions. This “From Tactics to Strategy” webinar focuses on helping you play a more critical role in your organization’s success. The fast-paced session reveals how you can capture and leverage the data gathered from across your financial systems to help senior management make better and faster strategic decisions.

The application economy has forced businesses to transform. To capture new growth opportunities, enterprises are opening up and sharing select data and applications with developers, partners, mobile devices, the cloud and the Internet of Things (IoT). One of the byproducts of this transformation is the discovery that legacy data has value in the application economy—so much so that new revenue opportunities emerge as this data is used in new ways.

Today’s smart computers can beat board game champions, master video games, and learn to recognize cats. No wonder artificial intelligence has captured the imaginations of business and IT leaders. And indeed, AI is starting to transform processes in established industries, from retail to financial services to manufacturing. Read this guide from Google Cloud and learn how you can unlock the transformational power of information and get useful insights from a vast and complex landscape of data.

Today’s smart computers can beat board game champions, master video games, and learn to recognize cats. No wonder artificial intelligence has captured the imaginations of business and IT leaders. And indeed, AI is starting to transform processes in established industries, from retail to financial services to manufacturing. Read this guide from Google Cloud and learn how you can unlock the transformational power of information and get useful insights from a vast and complex landscape of data.

Despite long-standing concerns captured in a myriad of surveys, security in the cloud has progressed to a more practical and achievable level. The cloud represents a shared security responsibility model whereby that responsibility is split between the Cloud Service Provider and the cloud customer. For organisations moving some or all of their applications and data to the cloud, acceptance of this model clears the way to more thoughtful consideration for how security can and should be architected — from the ground up. As a result, IT and IT Security leaders now have a much clearer trajectory to support their business operations in the cloud in a secure manner.

To compete in today’s fast-paced business climate, enterprises need accurate and frequent sales and customer reports to make real-time operational decisions about pricing, merchandising and inventory management. They also require greater agility to respond to business events as they happen, and more visibility into business activities so information and systems are optimized for peak efficiency and performance. By making use of data capture and business intelligence to integrate and apply data across the enterprise, organizations can capitalize on emerging opportunities and build a competitive advantage. The IBM® data replication portfolio is designed to address these issues through a highly flexible one-stop shop for high-volume, robust, secure information replication across heterogeneous data stores. The portfolio leverages real-time data replication to support high availability, database migration, application consolidation, dynamic warehousing, master data management (MDM), service