Tag: data governance
Tax authorities may not be everyone’s favourite organisations. But around the world, they have a key role in collecting revenues that enable governments to spend money on essential public services. You only need to read the media coverage of the tax avoidance of some of the big tech companies, and
Welche Rolle Datenqualität und Data Governance beim Data Management für Analytics spielen, habe ich mit meinem Kollegen Gerhard Svolba zuletzt an dieser Stelle diskutiert. Doch was genau macht modernes Datenmanagement aus, und welche Rolle spielen dabei neue Technologien à la Hadoop und Co.? Und wie sieht überhaupt die künftige Zusammenarbeit
Data-driven businesses outperform competitors. Matt Magne says SAS Data Governance and SAS MDM can help you get there.
Dylan Jones says spend time setting a vision of how to transform your data landscape – not debating definitions.
Over the past 6 weeks, the SAS Data Management team has been on our GDPR roadshow. In addition to customer meetings, we were also privileged to meet academics and journalists who are helping customers navigate implementation choices. In Slovenia, I had the opportunity to reflect with Miran Varga for Delo
Analise Polsky says analytics success for midsize business depends on getting the basics right and maintaining a data focus.
In just a few short months the European General Data Protection Regulation becomes enforceable. This regulation enshrines in law the rights of EU citizens to have their personal data treated in accordance with their wishes. The regulation applies to any organisation which is processing EU citizens’ data, and the UK
Like getting into good shape, Jim Harris says we must carefully measure adherence to regulatory compliance – using both internal and external measures.
We move closer to the implementation of the General Data Protection Regulation (GDPR) in May 2018. SAS colleagues have been writing about its effects, and what actions companies can take to address these issues. Looking at these articles, I found myself reading a story behind these articles. Kicking off the
Platform and strategy are core to compliance, but Jim Harris says commitment from people across the organization is just as important and harder to achieve.
David Loshin describes three sets of policies required for ensuring compliance with data protection directives for health care.
Q&A between Ulrike Bergmann and Carsten Krah The concept of self-service in analytics is often associated with business innovation and speed of response to customer demand. But self-service can also empower and encourage individual employees to support operations in a more effective way. I caught up with Carsten Krah Senior
The fight against fraud has to be at all levels, and use all possible means available to the organization. However, it is important to distinguish between political, organizational and technical means. Persuading states to organize themselves better to facilitate exchange of information between administrations can be decisive, even with the
Corporate compliance with an increasing number of industry regulations intended to protect personally identifiable information (PII) has made data privacy a frequent and public discussion. An inherent challenge to data privacy is, as Tamara Dull explained, “data, in and of itself, has no country, respects no law, and travels freely across borders. In the
The term compliance is most often associated with control. It evokes visions of restrictions, regulations and security protecting something which is to remain private. The term open is most often associated with access, and it evokes visions of an absence of restrictions, regulations and security – making something available which is
Achieving GDPR compliance is impossible without Data Management and Data Governance. That's a bold statement but it is borne out by any in-depth examination of the tasks necessary to achieve compliance. Let's take a look at a few of the things that regulators require when interacting with organizations around personal
I've been working on a pilot project recently with a client to test out some new NoSQL database frameworks (graph databases in particular). Our goal is to see how a different storage model, representation and presentation can enhance the usability and ease of integration for master data indexes and entity
As the application stack supporting big data has matured, it has demonstrated the feasibility of ingesting, persisting and analyzing potentially massive data sets that originate both within and outside of conventional enterprise boundaries. But what does this mean from a data governance perspective?
.@philsimon looks at the challenges and opportunities that big data pose for data governance.
Data governance seems to be the hottest topic at data-related conferences this year, and the question I get asked most often is, “where do we start?” Followed closely by how do we do it, what skills do we need, how do we convince the rest of the organisation to get
During a data quality assessment, one of my clients discovered that a large chunk of data that ultimately fed into their business analytics engine was sourced externally. After examining the contracts surrounding this data, I found that 100% of it failed to possess service-level agreements (SLAs) for the quality of
Karen, in unserem letzten Gespräch haben wir über die Bedeutung von professionellem Datenqualitäts-Management und über die erforderliche organisatorische Einbettung gesprochen. Jetzt möchte ich etwas konkreter werden. Beschreibe doch mal, worauf es bei der Umsetzung ankommt? Wie sollte sich ein solcher Data Governance Prozess gestalten?
I was surprised to learn recently that despite the reams of laws and policies directing the protection of personally identifiable information (PII) across industries and government agencies, more than 50 million Medicare beneficiaries were issued cards with a Medicare Beneficiary Number that's based on their Social Security Number (SSN). That's
Historically, before data was managed it was moved to a central location. For a long time that central location was the staging area for an enterprise data warehouse (EDW). While EDWs and their staging areas are still in use – especially for structured, transactional and internally generated data – big
Data quality initiatives challenge organizations because the discipline encompasses so many issues, approaches and tools. Across the board, there are four main activity areas – or pillars – that underlie any successful data quality initiative. Let’s look at what each pillar means, then consider the benefits SAS Data Management brings
Balance. This is the challenge facing any organisation wishing to exploit their customer data in the digital age. On one side we have the potential for a massive explosion of customer data. We can collect real-time social media data, machine data, behavioural data and of course our traditional master and