Helmut Plinke explains why modernizing your data management is essential to supporting your analytics platform.
SAS Data Connector to Oracle lets you easily load data from your Oracle DB into SAS Viya for advanced analytics. SAS/ACCESS Interface to Oracle (on SAS Viya) provides the required SAS Data Connector to Oracle, that should be deployed to your CAS environment. Once the below described configuration steps for
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
We all have challenges in getting an accurate and consistent view of our customers across multiple applications or sources of customer information. Suggestion-based matching is a technique found in SAS Data Quality to improve matching results for data that has arbitrary typos and incorrect spellings in it. The suggestion-based concept
Have you ever had problems matching data that has typographical errors in it? Because of the nature of arbitrary typos and incorrect spelled words a specific matching technique is required to tackle those cases. SAS Data Quality, with its traditional, in nature deterministic matching approach is by nature not best
In 2014, big data was on everyone’s mind. So in 2015, I expected to see data quality initiatives make a major shift toward big data. But I was surprised by a completely new requirement for data quality, which proves that the world is not all about big data – not
Utilizing big data analytics is currently one of the most promising strategies for businesses to gain competitive advantage and ensure future growth. But as we saw with “small data analytics,” the success of “big data analytics” relies heavily on the quality of its source data. In fact, when combining “small” and “big” data
I have participated in many discussions about master data management (MDM) being “just” about improving the quality of master data. Although master data management includes the discipline of data quality, it has a much broader scope. MDM introduces a new approach for managing data that isn't in scope of traditional data quality