Jim Harris says learn the lineage of the data that fed the analysis before you get dazzled by visualizations or algorithms.
Get faster value out of your data by empowering business users to work with data on their own.
As the application stack supporting big data has matured, it has demonstrated the feasibility of ingesting, persisting and analyzing potentially massive data sets that originate both within and outside of conventional enterprise boundaries. But what does this mean from a data governance perspective?
In the previous three blogs in this series, we talked about what metadata can be available from source systems, transformation and movement, and operational usage. For this final blog in the series, I want to discuss the analytical usage of metadata. Let’s set up the scenario. Let's imagine I'm a
As I discussed in the first two blogs of this series, metadata is useful in a variety of ways. Its importance starts at the source system, and continues through the data movement and transformation processes and into operations. Operational metadata, in particular, gives us information about the execution and completion
In the first blog of this four-part series, we discussed traditional data management and how we can apply these principles to our big data platforms. We also discussed how metadata can help bridge the gap of understanding the data as we move to newer technologies. Part 2 will focus on
Traditional data management includes all the disciplines required to manage data resources. More specifically, data management usually includes: Architectures that encompass data, process and infrastructure. Policies and governance surrounding data privacy, data quality and data usage. Procedures that manage a data life cycle from creation of the data to sunset
Lately I've been binge-watching a lot of police procedural television shows. The standard format for almost every episode is the same. It starts with the commission or discovery of a crime, followed by forensic investigation of the crime scene, analysis of the collected evidence, and interviews or interrogations with potential suspects. It ends
In a couple of my previous blogs I discussed how to audit who made changes to data in a SAS environment. In the last couple of weeks I have been asked how to do the same thing for SAS Visual Analytics reports and explorations. The Visual Analytics administrator overview report
Ever been stumped as you tried to find something in a huge, complex data environment that encompasses a hybrid of all types of internal and external data? It used to be that data systems were tactical, technically focused systems that provided point-to-point data access. In that era, it wasn’t so
It’s obvious that an enterprise data strategy involves data – but we sometimes disregard the fact that it should also involve metadata. Why? Because it’s key to unlocking the value of data. Metadata shows you what data is available and how people can use it. It also reveals which data
Jeff Stander passes along some of the lessons he's learned about third-party metadata collection.
I don’t know about you, but I'm asked every day where some type of data lives in our enterprise. I keep thinking that we have not done a good job of helping people learn to help themselves! A few things I have learned about corporate data assets are: The data
Integrating big data into existing data management processes and programs has become something of a siren call for organizations on the odyssey to become 21st century data-driven enterprises. To help save some lost time, this post offers a few tips for successful big data integration.
In a SAS Environment there is a lot of metadata, metadata about configuration such as server definitions, users, groups and roles and metadata about content like data, reports and jobs etc. SAS Administrators often want to report on metadata. They want to know what reports have been developed and where they are stored, what
In recent years, we practitioners in the data management world have been pretty quick to conflate “data governance” with “data quality” and “metadata.” Many tools marketed under "data governance" have emerged – yet when you inspect their capabilities, you see that in many ways these tools largely encompass data validation and data standardization. Unfortunately, we
‘Tis the season. While the season means different things to different people, its most common theme is people buying things for people. Things that become presents when they are covered in wrapping paper. Two retailers have been running television commercial campaigns this season about how presents are wrapped. One campaign
Data. It's everywhere. It can reside in many places through replication, accessibility needs or infrastructure costs. For reporting, that same data can be structurally changed (denormalized or aggregated) into additional reporting and analytic data repositories. Over time, new sources of enrichment of that data become available through traditional data sources
Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines
Recently, as I was driving in listening to National Public Radio (NPR), the topic of conversation was Edward Snowden and the National Security Agency (NSA), again. If you’ve been listening to any of this coverage, it seems the news media has a new catch word “metadata” that they are throwing
SAS Environment Manager 2.1 (which was released with SAS 9.4 M1), has new features to make it easier to manage your SAS environment. For example, it now supports metadata clusters, and it has an improved method for handling access to the application. But the biggest change is in metadata access.
In November, I resumed the “it’s all about the data” series, laying a foundation for helping SAS administrators understand how SAS stores and manages data for use in business intelligence and analytic applications. For this article, I culled our internal Thotwave knowledge base and queried our consultants who get questions
In my previous post, I used a game show metaphor for one aspect of metadata management, namely making sure table definitions are not ambiguously labeled. In this post, I will use name tags as a metaphor to discuss an important intersection of metadata management and master data management (MDM), an
The second part of my data governance primer series addresses ways to "mind your metadata." I can just hear the collective groans, and perhaps a stifled yawn. Sorry, but metadata collection is one of those necessary evils that may not be fun, but having it available as a resource to