SAS 9.4 maintenance release 5 was released on Sept 19, 2017. This release includes many new items including integration with SAS Viya and SAS Studio, a web application for SAS development. Also Included with this release are some cool new features in the graphics domain, some of which were requested
Manufacturing
‘Quality‘ means many things to many people. It’s subjective and depends on the industry and product being made, but the fundamental objective is to provide the best product to the right standard associated to fit, form and function. And cost and required profit margin must also be taken into account.
On a recent visit to an In-House Users Group meeting at a Pharmaceutical company, I presented a 1/2 day seminar on creating Clinical Graphs using SG Procedures. Polling the audience for their experience with these procedures indicated that many SAS users are not familiar with these new ways to create graphs. So,
Depending on who you speak with you will get varying definitions and opinions regarding demand sensing and shaping from sensing short-range replenishment based on sales orders to manual blending of point-of-sales (POS) data and shipments. Most companies think that they are sensing demand when in fact they are
ODER: Wie erstelle ich ein Edge Analytics Case auf Basis von SAS ESP, SAS Streamviewer und eines Modelltrucks? Das beschreibe ich in Teil 3. Rückblick: Im ersten Teil wurden die Idee und der Inhalt der SAS Streaming-Analytics-Demo beschrieben. Im zweiten Teil sind die einzelnen technischen Komponenten sowie die Software aufgelistet. Im
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
In the recent article, “Price-bots can collude against consumers,” the Economist discusses the consumer effects of prices set by price-bots. The article starts with an example of gasoline pricing strategies on Martha’s Vineyard. With a small number of gas stations on the island, the price-bots can cover all competitor prices frequently
Robots - everyone has probably been fascinated by the idea of robots at one time or another. From the early science fiction robots (such as Klaatu's robot Gort) to the mid-1980s movie robots (like Johnny 5), they have been portrayed in many different ways in fiction. These days, with the
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,
“I do not like this modern technology,” said my father-in-law. “It is making people too lazy. Things are too easy now.” He was referring to my grocery order. I was sitting in his kitchen in Reykjavik, Iceland, the day before my return to the United States. I had just explained
Employment - that's been a hot topic here in the US lately. Many of the manufacturing jobs we had in past decades are gone now, and it would be great if there was a crystal ball to predict which jobs might be at risk of disappearing in the future. The
Carbon Dioxide ... CO2. Humans breathe out 2.3 pounds of it per day. It's also produced when we burn organic materials & fossil fuels (such as coal, oil, and natural gas). Plants use it for photosynthesis, which in turn produces oxygen. It is also a greenhouse gas, which many claim
최근 금융, 통신, 자동차, 공공, 리테일, 교육 등 모든 산업을 관통하고 있는 한 단어가 있습니다. 바로 4차 산업혁명인데요. 빅데이터, 사물인터넷(IoT), 인공지능(머신러닝), 로봇 등 첨단 ICT 기술의 융합으로 완성되는 4차 산업혁명은 미래 산업의 필수 성장 동력으로 자리잡았습니다. 그 중에서도 특히 제조업은 이른바 ‘인더스트리 4.0’의 촉발과 함께 그 새로운 혁명의 시작을 알렸는데요.
Let me start by posing a question: "Are you forecasting at the edge to anticipate what consumers want or need before they know it?" Not just forecasting based on past demand behavior, but using real-time information as it is streaming in from connected devices on the Internet of Things (IoT).
Ya no se trata de imaginar cosas. Cada día las empresas enfrentan miles de desafíos. Desde decisiones de negocio hasta procesos operativos, pasando por la manera de relacionarse con sus clientes o de preparar los informes de cumplimientos regulatorios o cuidarse de los ataques o fraudes. No son escenarios que
To stack the deck means to cheat or to fix something so a desired outcome is achieved. This term originated in card games, but can also be applied to other things. And here, I apply it (both metaphorically and literally) to creating a better graph! I recently saw the following
„Durchsatz ist wichtig, jaja“, Supply-Chain-Leiter Herr Aklit lehnt sich zurück, faltet seine Hände über dem üppigen Bauch und sagt zu Lenin: „Sie haben ja schon einiges in Fluss gebracht mit Ihren Projekten zur Datenanalyse im Internet of Things.“ Er atmet tief durch und schaut aus dem Fenster: „Alles fließt …“,
When presenting information in form of a graph we show the data and let the reader draw the inferences. However, often one may want to draw the attention of the reader towards some aspect of the graph or data. For one such case, a user asked how to highlight one
Are you caught up in the machine learning forecasting frenzy? Is it reality or more hype? There's been a lot of hype about using machine learning for forecasting. And rightfully so, given the advancements in data collection, storage, and processing along with technology improvements, such as super computers and more powerful
Sagen wir es, wie es ist! Beginnt ein Text mit In Zeiten von Globalisierung und Digitalisierung, mag das bei vielen Lesern mittlerweile heftige Verstimmungen auslösen und wenig Lust auf Weiterlesen machen. Ständig wird von irgendwelchen Experten erklärt, dass es allerhöchste Eisenbahn für den nächsten digitalen Schritt sei. Im Grunde müsste
In nahezu einem Jahr findet die neue EU-Datenschutz-Grundverordnung (DSGVO) Anwendung. Wer bisher dachte, das hat noch Zeit und wird nicht so heiß gegessen, wie es gekocht wird, der wurde von der Ankündigung des Bayerischen Landesamts für Datenschutzaufsicht überrascht: Bayern kündigt schon erste Kontrollbesuche an. „Abwarten und nichts tun ist mehr
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
Recently I backed into a hotel parking spot after returning from a customer dinner. It was dark and rainy, and I was tired from traveling. My mind wandered until I heard a shrill “BEEP BEEP BEEP” coming from my rental car. I looked down at the dashboard’s rear-view camera, and
Building cars is towards the top of the manufacturing hierarchy - some countries are even known for the cars they build. If you want a good quality car, you probably think of Japan. If you want a stylish sports car, you probably think of Italy. If you want a diesel
„Wer 100% sicher sein will, ist 100% zu spät.“ Diesen Satz habe ich letztens auf dem IoT Forum in München gehört. Er fasst gut das Gefühl zusammen, dass mich in der deutschsprachigen Industrie 4.0 Debatte beschleicht. Die Buzz-Word-Schlachten der letzten 48 Monate haben ihre Wirkung nicht verfehlt: Kaum ein Strategiepapier
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
The widespread adoption of the term "analytics" reminds me of the evolution of the term "supply chain management." Initially the term focused on supply chain planning. It involved demand and supply balancing and the heuristics and optimization tools that came out of advanced planning and scheduling. Over time practically everything was included
Kennen Sie Kevin Ashton? Der britische Technologie-Pionier hat am Massachusetts Institute of Technology (MIT) einen internationalen Standard für RFID mitbegründet. Was aber vielleicht noch wichtiger ist: Vor fast 20 Jahren hatte er eine Vision von Computern, die Informationen über Gegenstände des Alltags und der Fabrikation sammeln und mit diesen Daten
Auch wenn der Hype von Gartner für beendet erklärt wurde: An Big Data und der Auswertung entsprechender (oftmals unstrukturierter) Datenmengen kommt kein Unternehmen vorbei. Doch welche Herausforderungen stellen Big Data und damit einhergehende Entwicklungen an das Data Management? Wie können Data Scientists, IT und Fachabteilung heute zusammenarbeiten? Und wo prallen
제조 업체들은 정치, 경제, 재무, 경쟁사 등 다양한 당면 과제 속에서 비즈니스를 운영하고 있습니다. 앞으로의 제조 환경도 글로벌 경제 위기 때만큼이나 불확실해 보이는데요. 그렇지만 제조업의 성장 기회는 분명 있을 것입니다. 최근 제조 산업에는 ‘인더스트리 4.0’이라는 새로운 시대의 막이 오르고 있습니다. 새 시대에는 자동화, 대규모 데이터, 분석이 사물인터넷(IoT), 클라우드 컴퓨팅과 융합하고, 가상 및