data management

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Published By: SAS     Published Date: Oct 27, 2014
Done correctly, data governance can transform the way an organization manages – and capitalizes on – its data. However, because it spans a variety of people, policies and technologies, data governance is a daunting effort. The SAS Data Governance Framework is designed to provide the organizational and technological structures needed to overcome common data governance failure points.
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data, data management, data governance, sas, white paper
    
SAS
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
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: DATAVERSITY     Published Date: Jan 23, 2013
No business likes to throw money out the window, or in the case of the modern day enterprise, down the electronic data stream. But, that is exactly what businesses all over the world are doing every day if they don’t have control of their data. This paper is sponsored by: ASG.
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white paper, dataversity, asg, metadata, business management, data, data management
    
DATAVERSITY
Published By: birst     Published Date: Jan 21, 2013
This Dive Deep analyst report looks at the process of building an environment for what can be aptly termed Agile Business Analytics.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
birst
Published By: birst     Published Date: Feb 22, 2013
The demand for business intelligence is strong and growing. For the past several years, BI has been repeatedly named as the top priority by Chief Information Officers (CIO) in Gartner’s annual CIO survey.
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white paper, dataversity, birst, business intelligence, cloud, cloud computing, analytics, data, data management
    
birst
Published By: SAP     Published Date: Jan 23, 2013
This paper examines the root causes of data centralization failure and then reviews straightforward best practices that can help avoid such failures but are typically ignored when systems are designed in an ad hoc, organic manner.
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data, data management, data governance, big data, cloud, business intelligence, semantic technology, nosql, information quality, data quality, metadata, enterprise information management, master data management, mdm, analytics, database
    
SAP
Published By: First San Francisco Partners     Published Date: Jan 23, 2013
Master data management (MDM) is about people and process; it is not about technology. Implementing MDM technology alone will not address operational and business process challenges.
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white paper, data, data management, master data management, first san francisco partners, dataversity
    
First San Francisco Partners
Published By: First San Francisco Partners     Published Date: Nov 20, 2013
One of the biggest challenges in a data management initiative is aligning different and sometimes competing organizations to work towards the same long-term vision. It is very difficult to execute a data management program all at once, or as a “big bang” approach. Rather, the program should be deployed in phases over time, starting in one area and incrementally building out and adding value to the rest of the organization over time.
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data, data management, enterprise information management, enterprise data management, white paper
    
First San Francisco Partners
Published By: First San Francisco Partners     Published Date: May 19, 2014
Master data management (MDM) is about people and process; it is not about technology. Implementing MDM technology alone will not address operational and business process challenges. Rather, “mastering” data involves people taking action through established data policies and processes. Data Governance ensures that data in the MDM hub is of high quality and can be trusted by business users. Lacking Data Governance, organizations do not have consistent data definitions or know what constitutes a data problem, who is accountable, what decisions need to be made, or how to escalate and resolve issues.
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white paper, master data management, first san francisco partners, kelle o'neal, dataversity, data governance, mdm, master data management white paper, data governance white paper
    
First San Francisco Partners
Published By: Adaptive     Published Date: Jan 24, 2013
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.
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data, data management, data governance, metadata, adaptive, dataversity, white paper
    
Adaptive
Published By: ASG     Published Date: Feb 05, 2013
No business likes to throw money out the window, or in the case of the modern day enterprise, down the electronic data stream. But, that is exactly what businesses all over the world are doing every day if they don’t have control of their data.
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white paper, dataversity, asg, metadata, business management, data, data management
    
ASG
Published By: ASG     Published Date: Jun 10, 2013
Everyone in an organization relies on Metadata to do their jobs. Whenever an email is sent, a report is run, inventory is ordered, compliance procedures are verified, a new IT system is integrated, applications are executed, or essentially any other business function, process, or decision is undertaken, Metadata is facilitating in the background. If that Metadata is corrupt, missing, redundant, or unpredictable then they cannot do their jobs well, they cannot trust the data they are using, and the organization ultimately suffers at all levels. Data Stewards are the people who are use, define, cleanse, archive, analyze, and share the data that is mapped directly to the Metadata of their myriad database and application systems. If your organization does not have Data Stewards (or an inefficient Stewardship Program), you need them.
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asg, data, data management, data governance, white paper, dataversity, data steward, metadata
    
ASG
Published By: MarkLogic     Published Date: Jun 16, 2013
The primary issue discussed within this paper boils down to two disparate database reliability models: ACID vs BASE. The first (ACID) has been around for some 30+ years, is a proven industry standard for SQL-centric and other relational databases, and works remarkably well in the older, yet still extant, world of vertical scaling. The second (BASE) has only recently gained popularity over the past 10 years or so, especially with the rise of social networking, Big Data, NoSQL, and other leviathans in the new world of Data Management. BASE requirements rose out of a need for ever-expanding horizontally scaled distributed networks, with non-relational data stores, and the real-time availability constraints of web-based transaction processing. While there are now more crossovers and negotiations between the two models, they essentially represent two competing groups, with Brewer’s CAP Theorem acting as the referee in the middle forcing tough decisions on each team.
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data, data management, unstructured data, nosql, database, acid, base, database transactioning
    
MarkLogic
Published By: Data Blueprint     Published Date: Apr 02, 2014
Organizations maintain data-based assets in hopes of successfully employing them in support of strategy. In an attempt to provide valued products and/or services, a customer relationship management (CRM) strategy should attempt to improve what is known about the wants and needs of existing customers. An organization may desire to transfer its inventory to its suppliers and to only play the role of transaction broker. A third strategy might be to use data to obtain significant efficiencies from productions/operations, ensuring a low cost advantage.
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data, data management, data value, return on investment, white paper
    
Data Blueprint
Published By: SAS     Published Date: Apr 02, 2014
Featuring use cases of various big data strategies, this paper explores several approaches and techniques that could be right for your enterprise, including using emerging big data platforms and creating new technology for problems not addressed by current big data platforms. It also covers moving more computation to traditional databases and implementing data virtualization.
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data, data management, big data, white paper, sas
    
SAS
Published By: Cambridge Semantics     Published Date: Apr 03, 2014
A new approach to rapid, high-quality data integration, data services, and data governance.
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white paper, data, data mangement, enterprise information management, cambridge semantics, semantic technology
    
Cambridge Semantics
Published By: Splice Machine     Published Date: May 19, 2014
SQL-on-Hadoop solutions have become very popular recently as companies solve the data access issues with Hadoop or seek a scale-out alternative for traditional relational database management systems. However, with all of the options available, choosing which solution is right for your business can be a daunting task. This white paper discusses the options you should consider and questions to ask, including: Is it really “Real-Time”? Is it true SQL? Does it support secondary indexes? Can it efficiently handle sparse data? Can it deliver fast performance on massive joins? Read this white paper to get a better understanding of the SQL-on-Hadoop landscape and what questions you should ask to identify best solution for your business.
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white paper, splice machine, sql, hadoop, nosql, nosql white paper, hadoop white paper, dataversity
    
Splice Machine
Published By: Semarchy     Published Date: Aug 18, 2016
David Loshin reexamines the way we ingest, manage, consume, and transform data into actionable information and intelligence. Read how this industry expert makes the case for data governance with an unconventional business-first focus. The conventional wisdom on data governance proposes hierarchies, operating models, and processes for data policy definition and implementation. Unfortunately, poorly-designed and minimally-planned data governance processes are ineffective because they are bureaucratic and overwhelming. This is especially true when processes are imposed by fiat, take a long time, and don't result in any short-term improvement in information value. But proper data governance is a critical success factor for master data management! In this paper, we examine the motivations for coupling data governance with master data management and consider how to evolve data policies and processes to position master data management for success.
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Semarchy
Published By: DATAVERSITY     Published Date: Jun 17, 2013
This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. “Data Governance” is a term fraught with nuance, misunderstanding, myriad opinions, and fear. It is often enough to keep Data Stewards and senior executives awake late into the night. The modern enterprise needs reliable and sustainable control over its technological systems, business processes, and data assets. Such control is tantamount to competitive success in an ever-changing marketplace driven by the exponential growth of data, mobile computing, social networking, the need for real-time analytics and reporting mechanisms, and increasing regulatory compliance requirements. Data Governance can enhance and buttress (or resuscitate,if needed) the strategic and tactical business drivers every enterprise needs for market success.
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research paper, data, data management, data governance, data steward
    
DATAVERSITY
Published By: Embarcadero     Published Date: Apr 23, 2015
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.
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data, data management, data modeling, agile, agile data modeling, it management
    
Embarcadero
Published By: Ted Hills     Published Date: Mar 29, 2016
NoSQL database management systems give us the opportunity to store our data according to more than one data storage model, but our entity-relationship data modeling notations are stuck in SQL land. Is there any need to model schema-less databases, and is it even possible? In this short white paper, Ted Hills examines these questions in light of a recent paper from MarkLogic on the hybrid data model. Ted Hills has been active in the Information Technology industry since 1975. At LexisNexis, Ted co-leads the work of establishing enterprise data architecture standards and governance processes, working with data models and business and data definitions for both structured and unstructured data. His book, NoSQL and SQL Data Modeling, was recently released by Technics Publications (http://technicspub.com).
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Ted Hills
Published By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state, governmental, decisions, data management
    
Aberdeen
Published By: Rubrik EMEA     Published Date: Jan 04, 2019
Rubrik Cloud Data Management is a single, unified software platform to manage your physical, virtual, and cloud data. With Rubrik, enterprises can drastically simplify their data protection processes, automate workflows, and migrate data to the cloud. The results are powerful: faster recoveries, easier management, no forklift upgrades, and hard dollars saved for other projects. Organizations pursuing cloudfirst policies can use Rubrik to archive to the cloud, create cloud DR capabilities, or perform cloud-native backup. And with Rubrik’s Polaris SaaS platform, it has never been easier to unify data across data centers and clouds, simplifying operations and governance. DATA
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Rubrik EMEA
Published By: Datastax     Published Date: Dec 27, 2018
Most enterprises operate in a hybrid cloud environment, whether they know it or not. The benefits of hybrid cloud and multi-cloud architectures are numerous, but since most companies don’t even realize they’re using multi-cloud, they’re not taking full advantage of the multi/hybrid cloud environment. Read this ebook to learn how proper data management via an enterprise data layer empowers enterprises to unlock the full potential of their multi- and/or hybrid cloud strategies to achieve data autonomy while scaling efficiently, effectively, and safely.
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Datastax
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