SAS Data Management helps organizations boldly go where no one has gone before

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As a youngster in the 70s and 80s, Star Trek inspired my imagination and fostered a great love for science, technology and reading. (See the embedded Star Trek infographic for some interesting factoids – did you know that there were 28 crew member deaths by those wearing red shirts?) Captain Kirk and the crew, especially the red shirts, had their fair share of challenges: advanced technology/firepower, cultural barriers/languages, and an onslaught of data they had to interpret in real time to make the right decision. They overcame these barriers with streamlined communication, organizational agility and advanced technology. How many CEOs do you see beaming down to customer sites?

Organizations today have similar data challenges: blending traditional data storage and processing technologies with emerging technologies like Hadoop, silos of teams and data, and a shortage of skilled resources to manage and derive value from it.

Any science fiction fan worth her salt will remember Star Trek's mission "to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before." Updates to the SAS Data Management portfolio help you to do just that – boldly go where no man or woman has gone before – by pushing your data beyond traditional boundaries to improve productivity, make better decisions faster and stave off competitive threats.

Boldly go where no one has gone before. (Infographic from sophie-the-vampire-slayer.tumblr.com)

To address these challenges, SAS has updated its data management suite of software, including SAS Event Stream Processing, SAS Data Loader for Hadoop and SAS Decision Manager.

The latest version of SAS Data Management empowers users to:

Drive better analytics with better data

You can make better decisions with analytics that are built on a strong, trusted data foundation. To do it, you need data management best practices – embedded within your current and future environment – that can deliver consistent, accurate and analytically valid data.

To help companies make better decisions in a big data world, SAS provides a common metadata and lineage framework that spans SAS Data Management and SAS Analytics. Why is this important? It helps you compress the time it takes to go from raw data to analytical model deployment. In addition, data quality functions run natively in both traditional and emerging sources, and these capabilities support many languages.

How is SAS rethinking data management? Let’s take a look at some of the newer developments.

Manage data beyond boundaries

Traditionally, data was confined to applications – and was the domain of the IT group. This isn’t how the world works anymore, though. Data scientists and other data analysts want, or need, access to data – wherever it resides and in whatever form it’s available.

SAS allows you to manage your data where it lives: in-stream, in-database, in-memory, in-cloud and in any other location. Managing data without moving it improves productivity and performance by giving you complete access to all your critical data while processes run in the most appropriate environment. For example, SAS Data Loader for Hadoop offers fast profiling and superb data quality functions – and you can run the same process in Spark or in Hadoop. You can also import third-party lineage like Erwin data models or ETL tools.

Awaken your data

Just like the Starship computer augmented Kirk's hunches, SAS provides built-in advanced analytics that can infuse your data with the “Power to Know.” Not only are we moving data management to the data, but we’re making data management smarter.

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Learn more about SAS Data Management.

A more adaptive, intelligent data management strategy can free IT to do more with your data management program. You can automate and augment manual data management tasks with machine learning techniques that reveal hidden issues, discrepancies and insights. SAS Data Quality lets you categorize data and extract meaningful values from both unstructured and semistructured text. And SAS Decision Manager can augment existing analytical models to improve decisions, providing you with a friendly interface and more algorithms to turn data into useful decisions.

We're excited about pushing the boundaries of a modern data management strategy. That’s why we've created a set of tools to help drive better analytics, manage data beyond boundaries and awaken your data. I wouldn't be surprised if the Starship Enterprise computer was running some form of SAS underneath the hood. Have the warp drives kicked in yet?

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About Author

Matthew Magne

Principal Product Marketing Manager

@bigdatamagnet - Matthew is a TEDx speaker, musician, and Catan player. He is currently the Global Product Marketing Manager for SAS Data Management focusing on Big Data, Master Data Management, Data Quality, Data Integration and Data Governance. Previously, Matthew was an Information Management Solutions Architect at SAS, worked as a Certified Data Management Consulting IT Professional at IBM, and is a recovering software engineer and entrepreneur. Mr. Magne received his BS, cum laude, in Computer Engineering at Boston University, has done graduate work in Object Oriented Development and completed his MBA at UNCW.

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