Data quality: The not-so-secret ingredient of customer data management
Kim Kaluba explains why good customer data management starts with trusted data quality.
Tag: data quality
Data retention strategy – Part 2
Don't be a data hoarder. Jim Harris shares guidelines for a data retention strategy.
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?
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.
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.
3 attributes that define a powerful analytics environment
In my last post I described "4 adaptability attributes for analytical success," and in the past I've discussed the strategic role analytics play in helping organizations succeed now and into the future. Now I'd like to discuss three attributes that define a powerful analytics environment: Speed Accuracy Scalability [NOTE: Any
Streaming to better data quality
Streaming technologies have been around for years, but as Felix Liao recently blogged, the numbers and types of use cases that can take advantage of these technologies have now increased exponentially. I've blogged about why streaming is the most effective way to handle the volume, variety and velocity of big data. That's
The yin and yang of better data and analytics
What are the most useful skills a data quality leader can possess? As an editor of an online data quality magazine, I naturally get asked this type of question regularly at events and meetups. My answer may surprise some who are expecting a data-centric response. I firmly believe that sales and
How Santa uses data quality to wrap up Christmas
"Two weeks to go," Santa said to himself, with millions of toys stacked up on the shelves. Each year worry hit at the same time – "How do I get the right toy to the right child without losing my mind?" Though Old St. Nick didn't have a computer science degree, deep down
Creating analytics? Don't forget a supplier SLA policy.
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
Managing data where it lives
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
How SAS supports the four pillars of a data quality initiative
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
Datenqualität im Zeitalter der Digitalisierung
Digitalisierung, Big Data, IoT, Smart Data – die Liste an Ansätzen, die den Klassiker „aus Daten mach Umsatz“ neu definieren wollen, wird länger und länger. An cleveren, schlüssigen und vielversprechenden Methoden mangelt es sicher nicht, ihnen allen gemein ist aber der mahnende Zeigefinger und ewige Spielverderber Datenqualität. Und wie das
The growing importance of big data quality
Our world is now so awash in data that many organizations have an embarrassment of riches when it comes to available data to support operational, tactical and strategic activities of the enterprise. Such a data-rich environment is highly susceptible to poor-quality data. This is especially true when swimming in data lakes –