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.
FCW : April 15, 2016
Data analytics has become a first-line defense for federal government agencies. Whether it’s identifying fraud and abuse, stopping hackers in their tracks, improving citizen service, reducing costs, or enhancing disaster response, using data analytics to better understand what’s happening in the world is a critical function these days. Without data analytics, the Defense Department wouldn’t have the real- time information it needs to keep the country and its soldiers safe. Government networks would be much more vulnerable to cyberthreats. The IRS wouldn’t have the proof it needs to ensure compliance with tax laws. And Health and Human Services wouldn’t have identified billions of dollars in questionable billing at 1,400 pharmacies. Data analytics uses sophisticated software to analyze and discover patterns in massive amounts of structured, semi- structured and unstructured data drawn from different systems. It’s an effective way to corral the large amounts of data sitting in different information silos, which traditionally have limited the ability to effectively share that data. Data analytics tools generally run on big data platforms. They can scale to incorporate more data as required. They can classify data based on specified attributes, divide large amounts of data into smaller segments that share attributes, and perform regression analysis to help identify relationships between variables. There are two basic types of data analytics: Predictive analytics mines data for patterns that can help predict future behaviors and situations. This type of analytics is extremely useful in predicting likely future events related to everything from security hacks to fraud detection. Prescriptive analytics bases its conclusions on the results of the predictive analytics, using it to suggest actions to remediate the predicted actions. For example, if predictive analytics suggests users with a specific profile are most likely to defraud a healthcare agency or the IRS, prescriptive analytics can then suggest ways to block those users or request additional verification from them. The result is actionable intelligence that helps government agencies understand what’s happening across their systems and technology infrastructure. This type of visibility provides a more holistic view of aggregated data. And this in turn provides more useful information that can help inform more accurate real- time decisions. The federal government clearly sees the value. More agencies are employing data analytics than ever before. This is bolstered by the 2012 Big Data Research and Development Initiative, which awarded six federal departments and agencies more than $200 million to better leverage digital data. According to a survey from Beacon Technology partners, data analytics is poised to become a major goal of government agencies, with the goal of productively maximizing the value of information. Data Analytics: More Important Than Ever Breakout: IoT and Data Analytics GameChanger DATA ANALYTICS CRITICAL FOR DATA DEFENSE SPONSORED REPORT DATA DRIVEN CYBERSECURITY The Internet of Things, or IoT, is all the rage today. The IoT refers to sensors and other devices with IP addresses that connect to the Internet and can send and receive data. They’re part of many current federal government operations. Smart buildings, for example, take advantage of temperature, energy consumption, air quality and even perimeter access control sensors. Logistics facilities use sensors to monitor inventory conditions and item location. Datacenters use sensors to diagnose and control equipment. On the battlefield, soldiers rely on sensor-enabled wearable devices such as augmented vision displays for real world and training scenarios. Internet-connected sensors are rapidly becoming a way of life in government, and they are just as quickly generating important data. By incorporating IoT data into a data analytics platform, agencies can improve efficiency, save money and improve security. For example, agencies can analyze data from government transport vehicles equipped with sensors to optimize routes and monitor fuel consumption. IT and building managers can receive alerts from connected devices that a part is about to fail. Then they can proactively replace it before the equipment fails to perform. Agencies can identify when systems or people are at risk from malfunctioning equipment and use patterns and trends to improve asset management, performance and maintenance. Internet-connected sensors are everywhere and their use will continue to grow over time. According to a December, 2014 report from IDC, 40 percent of IoT-created data will be stored, processed, analyzed and acted upon close to or at the edge of the network. As the growth of the IoT throughout government skyrockets, it will become more important than ever to make that data available to data analytics platforms. 0316_GameChanger_ClearShark_Splunk_NetApp_final.indd 1 3/17/16 12:49 PM
March 30, 2016
April 30, 2016