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Published By: DATAVERSITY     Published Date: Jul 24, 2014
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.
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data, data management, cognitive computing, machine learning, artificial intelligence, research paper
    
DATAVERSITY
Published By: DATAVERSITY     Published Date: Jul 06, 2015
The growth of NoSQL data storage solutions have revolutionized the way enterprises are dealing with their data. The older, relational platforms are still being utilized by most organizations, while the implementation of varying NoSQL platforms including Key-Value, Wide Column, Document, Graph, and Hybrid data stores are increasing at faster rates than ever seen before. Such implementations are causing enterprises to revise their Data Management procedures across-the-board from governance to analytics, metadata management to software development, data modeling to regulation and compliance. The time-honored techniques for data modeling are being rewritten, reworked, and modified in a multitude of different ways, often wholly dependent on the NoSQL platform under development. The research report analyzes a 2015 DATAVERSITY® survey titled “Modeling NoSQL.” The survey examined a number of crucial issues within the NoSQL world today, with focus on data modeling in particular.
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DATAVERSITY
Published By: Erwin     Published Date: Sep 13, 2018
Do you know what data you have, where it is and how to wring all the possible value from it? By harmonizing your data management and data governance efforts, you can accelerate your time to data preparation, data visibility and data-driven insights. Then you’ll know how to get the results you need.
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Erwin
Published By: Embarcadero     Published Date: Jul 23, 2015
Whether you’re working with relational data, schema-less (NoSQL) data, or model metadata, you need a data architecture that can actively leverage information assets for business value. The most valuable data has high quality, business context, and visibility across the organization. Check out this must-read eBook for essential insights on important data architecture topics.
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Embarcadero
Published By: Cloudant - an IBM Company     Published Date: Jun 01, 2015
Whether you're a DBA, data scientist or developer, you're probably considering how the cloud can help modernize your information management and analytics strategy. Cloud data warehousing can help you get more value from your data by combining the benefits of the cloud - speed, scale, and agility - with the simplicity and performance of traditional on-premises appliances. This white paper explores how a cloud data warehouse like IBM dashDB can reduce costs and deliver new business insights. Readers will learn about: - How data warehousing-as-a-service helps you scale without incurring extra costs - The benefits of in-database analytics in a cloud data warehouse - How a cloud data warehouse can integrate with the larger ecosystem of business intelligence tools, both on prem and off prem
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nosql, ibm, dashdb, database, cloud
    
Cloudant - an IBM Company
Published By: CMMI Institute     Published Date: Sep 03, 2014
To drive strategic insights that lead to competitive advantage, businesses must make the best and smartest use of today’s vast amount of data. To accomplish this, organizations need to apply a collaborative approach to optimizing their data assets. For organizations that seek to evaluate and improve their data management practices, CMMI® Institute has developed the Data Management Maturity (DMM)? model to bridge the perspective gap between business and IT. Download the white paper Why is Measurement of Data Management Maturity Important? to enable you to: - Empower your executives to make better and faster decisions using a strategic view of their data. - Achieve the elusive alignment and agreement between the business and IT - Create a clear path to increasing capabilities
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white paper, enterprise data management, data model, data modeling, data maturity model, cmmi institute
    
CMMI Institute
Published By: AT&T     Published Date: Sep 11, 2014
The age of Big Data is upon us. Storage costs are going down, and data analytics is becoming more capable and more user-friendly. Even your auto mechanic will be storing a petabyte of data soon. Big Data will give businesses new insights and help improve operations. With these new tools come questions about how to use them. But your mechanic knows more about fixing a transmission than developing a Hadoop cluster, and similar concerns hold true for larger enterprises. Businesses everywhere are looking for guidance.
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AT&T
Published By: Skytree     Published Date: Nov 23, 2014
Critical business information is often in the form of unstructured and semi-structured data that can be hard or impossible to interpret with legacy systems. In this brief, discover how you can use machine learning to analyze both unstructured text data and semi- structured log data, providing you with the insights needed to achieve your business goals.
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log data, machine learning, natural language, nlp, natural language processing, skytree, unstructured data, semi-structured data, data analysis
    
Skytree
Published By: Neo Technology     Published Date: Jun 28, 2015
The future of Master Data Management is deriving value from data relationships which reveal more data stories that become more and more important to competitive advantage as we enter into the future of data and business analytics. MDM will be about supplying consistent, meaningful views of master data and being able to unify data into one location, especially to optimize for query performance and data fit. Graph databases offer exactly that type of data/performance fit. Use data relationships to unlock real business value in MDM: - Graphs can easily model both hierarchical and non-hierarchical master data - The logical model IS the physical model making it easier for business users to visualize data relationships - Deliver insights in real-time from data relationships in your master data - Stay ahead of the business with faster development Download and read the white paper Your Master Data Is a Graph: Are You Ready? to learn why your master data is a graph and how graph databases like Neo4j are the best technologies for MDM.
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database, nosql, graph database, big data, master data management, mdm
    
Neo Technology
Published By: Trillium Software     Published Date: Apr 10, 2017
For the 11th consecutive year, the Gartner Magic Quadrant for Data Quality Tools1 research report positions Trillium Software as a leader in the Data Quality Software industry. Data Quality is vital to ensuring trust in your data-driven, decision making business processes. Confidence is the result of a well thought out and executed data quality management strategy and is critical to remaining competitive in a rapidly and ever-changing business world. The 2016 Gartner Magic Quadrant for Data Quality Tools report is a valuable reference, providing the latest insights into the strengths and cautions of leading vendors. Access the report to learn how a leading data quality solution can help you achieve your long-term strategic objectives.
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Trillium Software
Published By: Reltio     Published Date: Feb 12, 2016
Reltio delivers reliable data, relevant insights and recommended actions so companies can be right faster. Reltio Cloud combines data-driven applications with modern data management for better planning, customer engagement and risk management. IT streamlines data management for a complete view across all sources and formats at scale, while sales, marketing and compliance teams use data-driven applications to predict, collaborate and respond to opportunities in real-time. Companies of all sizes, including leading Fortune 500 companies in healthcare and life sciences, distribution and retail rely on Reltio.
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Reltio
Published By: Looker     Published Date: Sep 27, 2017
Creating metrics to measure the success or failure of your business may seem simple, but there are many avoidable mistakes that business leaders make every day. Many leaders end up focusing on “vanity metrics”, which might make the business look healthy, but do not actually give you insights into what is going on. And worst case, they are masking larger issues that you need to know and should be addressing. In this report, learn from other data-driven businesses how to avoid vanity metrics and focus on metrics that matter.
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Looker
Published By: IDERA     Published Date: Nov 07, 2017
Data modeling is all about data definition but has a much wider impact on the data of your organization. Quality data definition impacts how data is produced and directly impacts how the data is or will be used throughout an organization. That means that we must proactively govern the process of how we define data, to establish a common understanding across the team. In this whitepaper, Robert Seiner describes how data modeling is a form of data governance and provides insights on the three actions of governing data.
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IDERA
Published By: Alteryx     Published Date: May 24, 2017
Spreadsheets are a mainstay in almost every organization. They are a great way to calculate and manipulate numeric data to make decisions. Unfortunately, as organizations grow, so does the data, and relying on spreadsheet-based tools like Excel for heavy data preparation, blending and analysis can be cumbersome and unreliable. Alteryx, Inc. is a leader in self-service data analytics and provides analysts with the ability to easily prep, blend, and analyze all data using a repeatable workflow, then deploy and share analytics at scale for deeper insights in hours, not weeks. This paper highlights how transitioning from a spreadsheet-based environment to an Alteryx workflow approach can help analyst better understand their data, improve consistency, and operationalize analytics through a flexible deployment and consumption environment.
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Alteryx
Published By: Experian     Published Date: Nov 03, 2015
It is critically important for businesses today to leverage data as a strategic asset, instead of allowing it to become an obstacle. As more and more organizations are trying to make smarter, data-driven decisions, they are discovering that their data management strategy may not be as mature as it needs to be. One major shift we are seeing is the implementation of a Chief Data Officer. Experian Data Quality recently conducted a research study of more than 250 Chief Information Officers (CIOs) and Chief Data Officers (CDOs) in the US about their data management practices, and the explosion of the CDO role. Key insights in the report include: - Tips for overcoming typical data challenges within your organization - The changing data management landscape and its affect on the CIO - The new and growing need for the CDO - And more!
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Experian
Published By: Data Blueprint     Published Date: Jul 15, 2013
The role of the chief data officer (CDO) is relatively new across the organizational landscape – 70% of current CDO positions were created in the last year alone! The past decade has seen a combination of events, forcing organizations to consider this increasingly important role.
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Data Blueprint
Published By: SAP     Published Date: Aug 14, 2018
Today, ERP is a cornerstone of many organisations’ tech infrastructure. Yet many of the solutions in play are legacy products, decades old and designed for an entirely different business landscape. With industry leaders expressing concern that out-of-date ERP solutions have now become an impediment to competitive business, IDC set out to uncover what exactly modern companies need from their ERP systems, and why SAP S/4Hana seems so well placed to deliver.
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SAP
Published By: Hewlett Packard Enterprise     Published Date: Jul 18, 2018
Discover HPE OneSphere, a hybrid cloud management solution that enables IT to deliver private infrastructure with public-cloud ease. With the proliferation of self-service, on-demand infrastructure, enterprise developers have come to expect infrastructure as a service. However, the constraints of existing infrastructure and tools make this mean heavier workloads for IT teams.
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Hewlett Packard Enterprise
Published By: Amazon Web Services     Published Date: Jul 25, 2018
What is a Data Lake? Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lakes are a new and increasingly popular way to store and analyze data that addresses many of these challenges. A Data Lakes allows an organization to store all of their data, structured and unstructured, in one, centralized repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand. Download to find out more now.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Defining the Data Lake “Big data” is an idea as much as a particular methodology or technology, yet it’s an idea that is enabling powerful insights, faster and better decisions, and even business transformations across many industries. In general, big data can be characterized as an approach to extracting insights from very large quantities of structured and unstructured data from varied sources at a speed that is immediate (enough) for the particular analytics use case.
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Amazon Web Services
Published By: SafetyCulture     Published Date: Aug 14, 2018
Consistency and customer experience are key to quality and profitability in retail. Manual reporting processes can be unwieldy and time-consuming, but bringing together all compliance procedures under one digital platform means fast, consistent and easy-to-access performance data. Using real-time insights into best practice improves the reporting of quality control, stock loss prevention, inspection processes, logistics and more – saving time, increasing efficiency and boosting customer satisfaction. Benefits include better branding through monitoring rollouts with uploaded photos and videos, protection against shrinkage through improved inspection processes and audits, and clearer visibility of issues which means a speedier response.
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SafetyCulture
Published By: Panaya     Published Date: Aug 09, 2018
You can succeed in your digital transfomation and deliver applications and services faster, better, and safely. How? With Enterprise Agile Delivery. Enterprise Agile Delivery brings a wealth of benefits to organizations and can be adopted by any Agile hybrid framework: SAFe, LESS, Nexus as well as Agile/lean frameworks like Scrum and Kanban. Yet to achieve Eneterprise Agile Delivery, enterprises need an easy to use modern ALM tool for quick and successful onboarding. Download this white paper to understand how the right solution will help you: • Strategiaclly align feature releases and backlogs with your overall business strategy • Identify and prioritize dev and test activities with visibility into project waves and portfolios • Make data-based decisons for safe releases with real-time insights and multidimensional views into delivery risks • Sync business, dev, QA and release teams around shared objectives with automated coordination and communication
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Panaya
Published By: Google     Published Date: Aug 23, 2018
To remain competitive, executives must embrace change and equip employees to do the same. Conrad Electric, a 95-year-old online retail company, took just 4 months to migrate to G Suite, providing 4,000 of their employees with more transparent and agile collaboration capabilities. Read this Google Cloud report and get insights to creating a culture where people — combined with productivity tools — can reach their full potential.
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Google
Published By: Google     Published Date: Aug 23, 2018
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.
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Google
Published By: CA Technologies EMEA     Published Date: Sep 12, 2018
To compete successfully in today’s economy, companies from all industries require the ability to deliver software faster, with higher quality, and reduced risk and costs. This is only possible with a modern software factory that can deliver quality software continuously. Yet for most enterprises, testing has not kept pace with modern development methodologies. A new approach to software testing is required: Continuous Testing. In the first session in a series, join product management leadership to gain in-depth insights on how by shifting testing left, and automating all aspects of test case generation and execution, continuous testing, it enables you to deliver quality software faster than ever. Recorded Feb 5 2018 49 mins Presented by Steve Feloney, VP Product Management CA Technologies
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continuous delivery, application delivery, testing, test data management
    
CA Technologies EMEA
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