by clicking on the page. A slider will appear, allowing you to adjust your zoom level. Return to the original size by clicking on the page again.
the page around when zoomed in by dragging it.
the zoom using the slider on the top right.
by clicking on the zoomed-in page.
by entering text in the search field and click on "In This Issue" or "All Issues" to search the current issue or the archive of back issues respectively.
by clicking on thumbnails to select pages, and then press the print button.
this publication and page.
displays a table of sections with thumbnails and descriptions.
displays thumbnails of every page in the issue. Click on a page to jump.
allows you to browse through every available issue.
GCN : October and November 2016
S-11 S -11 ADVANCED ANALYTICS: THE ROAD AHEAD The field of advanced analytics is likely to expand in ways agencies can’t even yet imagine. Still, new and emerging tools suggest some important new directions. ENTERPRISE DATA HUBS When it comes to launching new initiatives, there’s no reason to start from scratch. An enterprise data hub provides a reliable platform for managing operations and security of advanced analytics initiatives. DATA INTEGRATION Advanced analytic initiatives are often stymied because potentially valuable data is spread across so many different silos. Enterprise-level NoSQL provides a means of storing, querying, and searching a wide array of structured and unstructured data. OPEN-SOURCE SOLUTIONS Solutions based on open source provide agencies with a way of building on cost-effective, proven technology without getting locked into proprietary technology. LOCATION-BASED INTELLIGENCE Social media feeds have become important data sources in many advanced analytics initiatives. In many cases, the value of social data increases significantly when enriched with user-defined location data. BIG TEXT From the early days of big data, experts have always discussed the value of mining text, but early solutions often failed to deliver meaningful results. A new generation of technology and methodology has begun to deliver on that promise. IN-MEMORY DATABASE The sheer volume of data involved in today’s advanced analytics initiatives can overwhelm traditional compute platforms. An in-memory database overcomes that obstacle, improving performance while reducing the data footprint and hardware and operational costs. VISUAL SEARCH Images and video often contain a wealth of information that goes untapped because of the sheer labor involved in sifting through all that material. That is changing, thanks to tools that automate the process of analyzing, indexing, and tagging visual content. MACHINE- GENERATED DATA Many agencies don’t realize the value or the volume of data generated by their IT infrastructures. This data can provide unparalleled insight into the performance and security of the IT enterprise. AUTOMATED DATA PREPARATION The intensive work needed to prepare data for analysis usually requires a data expert, which often creates a nearly insurmountable logjam. The more that process can be automated, the more quickly an agency can get initiatives off the ground. SPONSORED CONTENT
August and September 2016
January and February 2017