Category: Business Intelligence

Feed: SAS Blogs. Author: Inge Krogstad. IT managers see the potential for cost-cutting from transitioning application development to open source software (OSS). Today, companies can hire recent college graduates with skills in open source development and avail themselves of the free software. But is all that glitters really gold? Users groups and more formal workgroups are experiencing an avalanche of new routines that have been made available. And users are now sharing programs along with their own cutting-edge ideas, whether based on R, Python, Tensorflow, or another programming language or library. Therefore, it has to be assumed that business leaders ... Read More

Feed: SAS Blogs. Author: David Loshin. In recent years, aspirations for achieving digital transformation objectives have inspired the emergence of new senior management roles such as the Chief Data Officer (CDO), the Chief Analytics Officer (CAO), and the Chief Information Security Officer (CISO).  These roles indicate a general recognition of organizational value of data as a (conceptual) asset. They also reflect the division of digital transformation into virtual operational silos: Data management versus analytics versus security, privacy, etc. Compartmentalizing these different facets of information management and governance perhaps does a disservice to the organization’s objectives for digital transformation. This is ... Read More

Feed: Actian. Author: Actian Corporation. We have just announced the findings of the Actian Datacast Hybrid Data Trends Survey which offers new insights into the current challenges and opportunities for data-driven organizations when it comes to managing hybrid data environments.The survey polled 303 IT professionals who have some influence or decision-making ability and work in a company with at least 250 employees. The infographic below outlines four key trends that emerged from this research around access to data, maximizing the value of data gathered and compliance. In the coming weeks, we will be publishing a four-part blog series that explores ... Read More

Feed: What's New. Author: Lindsay Betzendahl. AboutInitially, I had this down the side, but after further thought, I realized I wanted the personal section to be the first someone would read. For me, it was important for people to read this biographical resume and feel like they know me—what makes me interesting, what I like, and why might you want me to work with you. Additionally, I wanted to give it more space because I chose to use some custom images I made in PowerPoint. Creating images to enhance a visualization is something I do a lot, so I wanted ... Read More

Feed: Actian. Author: Lewis Carr. Extract, Transform, and Load (ETL) is the process that has been used to share data between applications, transactional systems, and data warehouses for decades.  It essentially works like this; you define an integration, pull the data out of the source system, use some mapping and aggregation rules to transform the data into the format needed by the target system and then you load (save) the data in the target system’s database.ETL Hell While this process seems simple and intuitive, it has a few problems that are leading many companies to question the sustainability of the ... Read More

Feed: What's New. Author: Anton Grinevskij. In order to predict my expenses in different cities, I am relying on the cost of living index. The index is a relative expensiveness of a city, expressed in percentage compared to New York City, which has a value of 100. Since my raw budget data has zip codes, not cities, I need a way to convert them. I’ll take advantage of the Python integration to programmatically look up the city that each zip code belongs to. This process is as simple as adding a script step, pointing it to a Python script file, ... Read More

Feed: Apple Machine Learning Journal. Author: . Many language-related tasks, such as entering text on your iPhone, discovering news articles you might enjoy, or finding out answers to questions you may have, are powered by language-specific natural language processing (NLP) models. To decide which model to invoke at a particular point in time, we must perform language identification (LID), often on the basis of limited evidence, namely a short character string. Performing reliable LID is more critical than ever as multi-lingual input is becoming more and more common across all Apple platforms. In most writing scripts — like Latin and ... Read More

Feed: SAS Blogs. Author: Joe Furbee. Editor’s note: This is the first article in a series by Conor Hogan, a Solutions Architect at SAS, on SAS and database and storage options on cloud technologies. This article covers the SAS offerings available to connect to and interact with the various database options available in Amazon Web Services. As companies move their computing to the cloud, they are also moving their storage to the cloud. Just like compute in the cloud, data storage in the cloud is elastic and responds to demand while only paying for what you use. As more technologies ... Read More

Feed: Feed | Tractica. Author: . Numerous customer service applications – from manufacturing to order fulfillment – require recognition of faces and objects. Customer service robots need to recognize faces and associate them with customer data to provide personalized assistance. Tasks that are simple for any human child had traditionally been quite difficult for robots. Cloud-Based Recognition Platforms Today, cloud-based systems like Amazon Rekognition enable enterprise robots to interpret their surroundings more accurately. Rekognition uses the Amazon Kinesis Video Streams robot OS (ROS) extension to stream live video data from the robots of AWS RoboMaker subscribers. It then identifies and ... Read More

Feed: SAS Blogs. Author: Rick Wicklin. An important application of nonlinear optimization is finding parameters of a model that fit data. For some models, the parameters are constrained by the data. A canonical example is the maximum likelihood estimation of a so-called "threshold parameter" for the three-parameter lognormal distribution. For this distribution, the objective function is the log-likelihood function, which includes a term that looks like log(xi - θ), where xi is the i_th data value and θ is the threshold parameter. Notice that you cannot evaluate the objective function for large values of θ. Similar situations occur for other ... Read More