Blend, cleanse and prepare data for analytics, reporting or data modernization efforts
Phil Simon chimes in on the tendency to rely upon these tools too much.
No es un golpe de suerte o una tendencia anómala la emitida por IDC que sustenta que entre 2015 y 2019 la inversión en tecnologías de análisis de datos crecerá un 50%, alcanzando en ese último año los US$187.000 millones. Tampoco lo es que para este año se estime que el
I’ve been making note of recent interactions and observations with different companies that I’ve done business with lately. My goal is to share with you real ways in which excellent customer experiences are shaped. Observation #1: Witty conversations rule As I write this, I’m sitting at a Panera Bread restaurant
Jim Harris says more reusable data quality processes mean less reliance on IT and higher productivity across the board.
Uno de nuestros firmes pensamientos es que el activo más valioso de las empresas son sus datos y el buen uso de ellos es el que pueden llevar a las compañías a una real transformación digital del negocio. A pesar de esto la consultora Gartner comenta que los líderes aún tienen una
To do their jobs well, Joyce Norris-Montanari says users doing analytical data preparation need access to both standardized and raw data.
David Loshin describes how data as a service supports fast deployment, easy accessibility and data reuse.
84412925 - business team investment trading do this deal on a stock exchange. people working in the office. Caminar por la calle y que su celular le dé una notificación de alguna promoción especial de ese almacén que le gusta, que está solo a algunos pasos de usted y en
Caminar por la calle y que su celular le dé una notificación de alguna promoción especial de ese almacén que le gusta, que está solo a algunos pasos de usted y en el que utilizando la tarjeta de crédito de su banco puede comprar a cero interés, no es un
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?
Get faster value out of your data by empowering business users to work with data on their own.
Phil Simon weighs in on the value of getting your own hands dirty using self-service data prep.
Managing big data doesn't always mean hiring more people and buying new tools.
Die EU-Datenschutz-Grundverordnung kommt näher – ausweichen oder draufhalten? In den letzten Wochen hatte ich die tolle Gelegenheit mit zahlreichen Kunden und Partnern über die neue EU-Datenschutz-Grundverordnung (DS-GVO) zu sprechen. Die Meinungen und Erwartungen sind dabei wirklich außerordentlich breit gefächert. Das ist nicht weiter verwunderlich, denn das Thema hat zuletzt stark an
David Loshin explains how to set up a data catalog that will help you get more value from a data lake.
모든 것을 실시간으로 실행하고, 실시간으로 평가하는 바야흐로 ‘스트리밍 시대’입니다. 길을 걷다가 들리는 음악을 그 자리에서 검색하고 스트리밍으로 재생해 듣습니다. 스마트폰 메신저나 소셜 미디어(SNS)를 통해 바로 공유할 수도 있죠. 월드컵과 올림픽 등 스포츠 경기는 물론 대선 토론과 개표 현황 등 정치 이벤트까지 케이블 TV나 페이스북 라이브를 통해 실시간으로 시청합니다. 기업에서는 어떨까요? 매월,
Get on with your day faster by taking a self-service approach to data preparation.
In this blog post I am going to cover the example of importing data into SAS Viya using Cloud Analytic Services (CAS) actions via REST API. For example, you may want to import data into a CASLib via REST API. This means you can perform an import of data outside
Analytics-driven forecasting means more than measuring trend and seasonality. It includes all categories of methods (e.g. exponential smoothing, dynamic regression, ARIMA, ARIMA(X), unobserved component models, and more), including artificial intelligence, but not necessarily deep learning algorithms. That said, deep learning algorithms like neural networks can also be used for demand forecasting,
The Cloud Analytic Server (CAS for short) is SAS’ latest high-performance, scalable, in-memory analytic data server. In this post, I’d like to discuss the CAS physical data model, i.e.what features CAS offers for data storage, and how to use them to maximize performance in CAS (and consequently SAS Visual Analytics
Phil Simon shares his thoughts on this simple yet often-overlooked question.
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?
If I’m having a tough week, I might feel sorry for myself for a minute or two. But to snap myself out of it, all I have to do is think of the data managers. Those folks have to contend with duplicate records, bad information, data proliferation, accountability, permissions, privacy,
Joyce Norris-Montanari says focus on data quality and governance, privacy and security when providing data on demand.
West Perth ist das „analytische“ Paradies. Das wissen wir nun dank des Projekts „Paradise Found“ und des Blogbeitrags meines Kollegen Andreas Becks. Klar ist, ohne Machine Learning und Analytics wären wir niemals anhand der untersuchten fünf Millionen Datenpunkte zu 148.233 Orten weltweit aus 1.124 Datenquellen auf den Stadtteil der australischen Boomtown
David Loshin recommends enforcing governed standards to help avoid conflicting analytical results.
When we talk about consent management for the EU’s General Data Protection Regulation (GDPR), one of the key considerations is “consent for a purpose.” It might have been sufficient in the past to provide a form with a single generic consent check box and store the fact that consent was
Jim Harris considers whether we can save private data in the age of big data.
Der Datenschutz macht‘s möglich: Customer Intelligence 360 geht in die nächste Dimension! Der Kunde360, „Omni-Channel“, „Data-driven Marketing“ – wer hat in den letzten zwölf Monat davon gehört? Oder, ich versuche es mal anders rum: Wer hat nicht davon gehört? Ja, richtig – wir sind im Bereich Customer Intelligence/Marketing. Und alles,
Todd Wright says Hadoop can be difficult – but data management can help.
