Data retention strategy – Part 2
Don't be a data hoarder. Jim Harris shares guidelines for a data retention strategy.
Tag: data quality
Data governance – The topic that never dies
Todd Wright says data governance is more relevant than ever – especially in light of the GDPR.
Data retention strategy – Part 1
Jim Harris asks: Do you retain and maintain data, or do you have a data retention strategy?
How to improve diagnostic coding through technology
Today it is possible to use freeform text from patient journals in data management to support healthcare professionals in their daily decision making. This blog post elaborates on how hospitals can automate their diagnostic coding to be more efficient, reduce errors, and improve quality and patient safety. This is the second blog
Cost factor data quality in insurance companies
Data quality is a topic that is often discussed in insurance, but also plays a subordinate role in the project day. I asked Karen Prillwitz about the importance of data quality at large insurers. For many years Karen has advised insurance companies, and as a project manager in a large
How to handle increasing demands for high-quality health care data
Excellent quality of patient treatment and patient safety is highly prioritised on the health care agenda in the Nordic countries. As a result, the demand for measuring quality has increased, and is closely followed by certain special demands for documentation and data quality. If not handled intelligently, this can be
Data quality monitoring - step 3.
In the previous posts of the series, there were described two first steps - data defining, and then their profiling. After precise data collecting and setting business rules, we can move on to their creating.
Monitorowanie jakości danych - krok 3.
W poprzednich postach z serii dotyczącej monitorowania jakości danych opisane zostały dwa pierwsze kroki - definiowanie danych, a następnie ich profilowanie. Po dokładnym zbadaniu danych i dopracowaniu reguł biznesowych, możemy przejść do ich faktycznego tworzenia.
Data quality monitoring – step 2.
The previous post in this series described the first step of the data monitoring process — defining. Therefore, once we have defined the objective of our initiative and, consequently, also data sources and specific requirements towards them, we can move on to studying the data.
Monitorowanie jakości danych - krok 2.
W poprzednim poście z tej serii opisany był pierwszy krok procesu monitorowania danych – tworzenie definicji. Dlatego kiedy już mamy zdefiniowany cel naszej inicjatywy, a co za tym idzie także źródła danych oraz określone wymagania względem nich, możemy przejść do zapoznania się z danymi.
The SAS platform – It all starts with data management
To get full value from analytics programs, Todd Wright says be sure you can first access, integrate, cleanse and govern your data.
Reusable data quality enables self-service data preparation
Jim Harris says more reusable data quality processes mean less reliance on IT and higher productivity across the board.
Data quality monitoring – step 1.
You have to be able to trust the data that you are working with, whether it’s data processing or analysis that you are involved with. And there is a strong correlation between that trust and data quality. Is it possible to determine data quality without monitoring mechanisms?
SAS Visual Analytics: Hallo Emilia – Goodbye Daniel
Die Geburtenrate in Deutschland befindet sich derzeit auf dem höchsten Niveau seit 33 Jahren. Eine erfreuliche Entwicklung, und zugleich stellt es Eltern vor die schwere Entscheidung, welchen Namen der Nachwuchs tragen soll. Zahlreiche Webseiten und Bücher bieten Hitlisten und Namensbeschreibungen an, um die Auswahl zu erleichtern. Oder sollte man das
Self-service data preparation gives fast access to the data you need
Get on with your day faster by taking a self-service approach to data preparation.
Monitorowanie jakości danych - krok 1.
Niezbędnym elementem wszystkich inicjatyw związanych z przetwarzaniem i analizowaniem danych jest zaufanie do danych, które w znacznej mierze uzależnione jest od ich jakości. Czy można określić jakość danych bez mechanizmów jej monitorowania?
The data governance path to AnaCredit
Many of the regulations coming into effect after 2010, are the result of the financial crisis that has significantly re-shaped the financial industry worldwide and especially in Europe. One of the major projects that has been undertaken by the statistics team of the ECB, launched in 2011, is the setup
Move "mountains" and build a trusted data foundation with SAS Data Quality
Matthew Magne describes how SAS Data Quality can help you build a trusted data foundation, one stone at a time.
On the way to data lakes and Hadoop – Part 1
Jim Harris advocates addressing data quality and governance issues on the way to data lakes and Hadoop.
Four ways SAS makes Hadoop easy
Clark Bradley explains how SAS can make Hadoop approachable and accessible.
Supporting and enabling tax authorities: the role of advanced analytics
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
The importance of data quality to MDM
Jim Harris explains why data quality is such a fundamental aspect of master data management.
Lenin überholt sich selbst im Internet of Tempo (IoT3)
Lenin und ich sitzen im Publikum und applaudieren heftig: Seine Chefin hat ihren Vortrag beendet über „Datenqualität als Erfolgsfaktor im Internet of Things“. „Kein Datenqualitätsprojekt ohne Hilfe von oben“, raunt Lenin mir zu, "Unterstützung vom Boss ist manchmal wichtiger als tolle Software." Ich will beleidigt darauf hinweisen, dass seine Chefin
Don't let data issues delay analytics
In a recent presentation, Jill Dyche, VP of SAS Best Practices gave two great quotes: "Map strategy to data" and "strategy drives analytics drives data." In other words, don't wait for your data to be perfect before you invest in analytics. Don't get me wrong -- I fully understand and
Data quality and data preparation in self-service
The rise of self-service analytics, and the idea of the ‘citizen data scientist’, has also brought a number of issues to the fore in organizations. In particular, two common areas of discussion are the twin pillars of data quality and data preparation. There is no doubt that good quality, well-prepared
Event stream processing, data quality and risk mitigation
David Loshin extends his exploration of ethical issues surrounding automated systems and event stream processing to encompass data quality and risk considerations.
Lenins Lächeln oder: Haferkekse im Internet of Trash (IoT2)
Lenin hatte gelächelt und von seinen Erfolgen im Internet of Things berichtet; richtig begeistert war er gewesen. – Aber jetzt murrt er: „Das ist alles Müll! Internet of Trash sollte es heißen! Die Daten stimmen nicht, die Leute schimpfen über das Projekt, der Fachbereich und meine Chefin sitzen mir im
Data privacy and governance: No easy answers
.@philsimon advises to be wary of those promising obvious and facile solutions to increasingly challenging governance and privacy issues.
The fight against fraud: the importance of analytics
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
Risk management's new stakeholders
We like to think about risk management as a specialist domain. Indeed, at SAS, we have a dedicated team that works with risk officers to exploit analytics for risk mitigation. But from my vantage across analytics platforms, analytics to support risk management has seen fascinating changes. The way that we think