Executives, managers and information workers have all come to respect the role that data management plays in the success of their organizations. But organizations don’t always do a good job of communicating and encouraging better ways of managing information. In this e-book you will find easy to digest resources on the value and importance of data preparation, data governance, data integration, data quality, data federation, streaming data, and master data management.
Complexity, globalization and digitalization are just some of the elements at play in the risk landscape—and data is becoming a core part of understanding and navigating risk.
How do modern finance leaders view, navigate and manage enterprise risk with data? Dun & Bradstreet surveyed global finance leaders across industries and business types. Here are the top trends that emerged from the study:
1. The Enterprise Risk & Strategy Disconnect—Finance leaders are using data and managing risk programs, but over 65% of finance leaders say there’s missing link between risk and strategy.
2. The Risks of the Use and Misuse of Data—Up to 50% of the data used to manage modern risk is disconnected. Only 15% of leaders are confident about the quality of their data.
3. Risky Relationships—Only 20% of finance leaders say the data they use to manage risk is fully integrated and shared.
Download the study to learn how finance leaders are approaching data and enterprise risk management
L’infrastructure Cloud, vous avez dû vous y mettre au début en prenant beaucoup de précaution… Vous avez probablement limité votre périmètre à un provisionnement rapide ou à une diminution des coûts matériels ou opérationnels.
Mais comment résister aux avantages de cette technologie ? Le cloud continue d’évoluer et de gagner en crédibilité dans tous les secteurs d’activité. Aujourd’hui, nous attendons de tous les systèmes d’entreprise qu’ils intègrent les avantages du cloud.
All’inizio, probabilmente avrai scelto di adottare l’infrastruttura cloud con una certa prudenza, limitandoti a un approvvigionamento rapido o alla riduzione dei costi operativi o delle macchine.
Ma come resistere ai vantaggi di questo nuovo modo di fruire della tecnologia? Il cloud continua a evolvere e a conquistare credibilità in tutti i settori. Oggi, ci aspettiamo che ogni sistema aziendale possa beneficiare dei vantaggi del cloud.
I progressi nel campo digitale rivoluzionano in profondità il nostro modo di lavorare, introducendo innovazioni nei nostri uffici praticamente ogni giorno. Queste tecnologie hanno alzato il livello delle aspettative, costringendo le aziende a operare con un'agilità senza precedenti.
Questi cambiamenti sono grandi opportunità, ma purtroppo ci imbattiamo anche in nuovi ostacoli che possono intralciare la nostra marcia verso il successo, come la necessità di innovare rapidamente, di minimizzare i costi e di reagire prontamente alle pressioni della concorrenza.
La tecnologia IaaS, un tempo vista con scetticismo da molti responsabili IT, viene oggi adottata da molte aziende, che trasferiscono sul cloud i workload e accantonano l’architettura locale che prima ritenevano indispensabile.
Nonostante i vantaggi in termini di prestazioni, flessibilità e opportunità di innovazione sperimentati dagli utenti che già hanno adottato questa tecnologia, alcune aziende ritardano la migrazione per paura del cambiamento.
Les avancées du numérique révolutionnent la manière dont nous travaillons, en apportant des innovations de façon permanente dans notre quotidien de travail. Ces technologies très prisées ont renforcé les attentes, obligeant les organisations à développer l'agilité métier à des niveaux sans précédent.
Même si les opportunités annoncées sont prometteuses, nous sommes confrontés à de nouveaux freins qui peuvent faire obstacle à la réussite, comme la nécessité d'innover rapidement, de minimiser les coûts et de répondre rapidement aux pressions exercées par la concurrence.
Pour réussir dans le contexte concurrentiel actuel, les entreprises doivent se liberer des limites inhérentes à leurs infrastructures informatiques existantes. L’époque de l’achat de matériel et de la gestion d’énormes centres de données pour faire fonctionner les systèmes informatiques est en train de prendre fin. La gestion et la maintenance des infrastructures sont tout simplement trop coûteuses.
Digital developments are forever shaping the way we work, bringing new innovations through our office doors almost every day. These high-demand technologies have increased expectations, with organizations now having to drive business agility at unprecedented levels.
Although we’re presented with enormous opportunity, we also face new obstacles that can block the path to success; obstacles such as the need to innovate quickly, keep costs down, and actively respond to competitive pressures.
To succeed in today’s competitive reality, businesses need to free themselves from the limitations of legacy IT infrastructure. The days of purchasing hardware and maintaining massive data centers to run IT must come to an end. Managing and maintaining your infrastructure is simply too expensive.
Explanation of the Oracle IaaS solutions and cases studies.
IT departments are under constant pressure to do more with less. Now, as well as keeping the lights on, they are expected to deliver projects that create real business value. As more businesses use digital technologies to disrupt their markets, this pressure is intensifying.
Infrastructure as a service (IaaS) is evolving against this background. Initially, it caught CIOs’ attention because it helped them cut costs. Today, IaaS underpins organizations’ agility in the face of disruption and drives innovation-led growth.
Marketing organizations are often limited in their ability to progress marketing tactics from single channel to cross-channel and real-time customer engagement. While marketing organizations might have a robust customer engagement strategy in place, often times there is a gap between their strategy and their ability to execute, with the right personalization and context that customers prefer. Over 62 percent of customers are always-on and readily addressable, but marketers aren’t implementing the right strategies to reach them.
This eBook discusses data-driven marketing tactics that can help marketers mind the gap – bridging customer strategy and ability to execute, with the right personalization and context that customers prefer.
ESG Lab performed hands-on evaluation and testing of the Hitachi Content Platform portfolio, consisting of Hitachi Content Platform (HCP), Hitachi Content Platform Anywhere (HCP Anywhere) online file sharing, Hitachi Data Ingestor (HDI), and Hitachi Content Intelligence (HCI) data aggregation and analysis. Testing focused on integration of the platforms, global access to content, public and private cloud tiering, data quality and analysis, and the ease of deployment and management of the solution.
According to Gartner, "supply chain leaders responsible for quality management are shifting to software solutions that standardize processes, optimize data and ensure compliance. This research provides guidance for structuring a process for QMS software selection."
Download this Gartner Analyst Guide to learn:
Key challenges in the QMS software selection processes
What to expect from different QMS solutions across the market
Analysis of the current state of quality management to help define software requirements
Self assessment questions and commonly sought QMS system functionalities to use in your decision making process
There has been no shortage of high profile recalls over the past several years. Suppliers are being required to provide more robust quality management systems, provide better real-time visablity into manufacturing data, and may even be held accountable for additional charge-back and warranty claims. Take a next generation approach to quality management.
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Cloud-based data presents a wealth of potential information for organizations seeking to build and maintain a competitive advantage in their industry. However, as discussed in “The truth about information governance and the cloud,” most organizations will be confronted with the challenging task of reconciling their legacy on-premises data with new, third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
The discipline of data quality assurance ensures that data is "fit for purpose" in the context of existing business operations, analytics and emerging digital business scenarios. It covers much more than just technology. It includes program management, roles, organizational structures, use cases and processes (such as those for monitoring, reporting and remediating data quality issues). It is also linked to broader initiatives in the field of enterprise information management (EIM), including information governance and master data management (MDM)
Published By: Claravine
Published Date: Jan 03, 2019
Marketers have long struggled with the simple task of knowing
which marketing spend is truly effective, and how to optimize that
spend. At the heart of the issue lies the challenge of ensuring the
data quality and consistency exists to make decisions based on
Why is this a problem? First, effective tracking is reliant on the
consistent, complete application of campaign tracking codes and
associated metadata, which has traditionally been a manual, ungoverned
process. Adding to this complexity has been the dramatic
expansion of digital marketing point solutions, and the disparate
teams expected to execute across each of these channels and geographies.
The result is what you would expect—highly inaccurate,
incomplete, and inconsistent data that must be manually cleaned
before reporting is possible.
Fortunately a solution exists. Progressive marketing leaders are
implementing Digital Experience Data Management (DXDM), ensuring
the rich, consistent insights critical to ma
We are offering this second edition resource as a business oriented, working guide to core data management practices. In this ebook you will find easy to digest resources on the value and importance of data preparation, data governance, data integration, data quality, data federation, streaming data, and master data management.
Published By: MarkLogic
Published Date: Mar 29, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools.
MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.