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<h3 class="h2 entry-title"><a href="../blog/apache-spot-product-architecture-overview/" rel="bookmark" title="Apache Spot: Three Most-Asked Questions">Apache Spot Product Architecture Overview</a></h3>
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<time class="updated entry-time" datetime="2017-03-27" itemprop="datePublished">
March 27, 2017
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<p>Data Sources - Spot can directly collect netflow data, DNS data and/or proxy data. This data can be collected also from a SIEM or from a common logging server. Additional data types can be collected using Open Data Model. Any number of data sources can be analyzed using Spot. Because most of these data sources represent a large volume of data, most organizations start with the data source that represents the area of highest risk.&#8230; <a class="excerpt-read-more" href="../blog/apache-spot-product-architecture-overview/" title="Read Apache Spot Product Architecture Overview">Read more &raquo;</a></p>
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<h1 class="h2 entry-title"><a href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" rel="bookmark" title="Strength in Numbers: Why Consider Open Source Cybersecurity Analytics">Strength in Numbers: Why Consider Open Source Cybersecurity Analytics</a></h1>
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<time class="updated entry-time" datetime="2016-10-21" itemprop="datePublished">
October 21, 2016
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By Rob Kent, Vice President of Marketing at Cybraics Competition is widely considered to be a healthy and positive thing, traditionally viewed as providing options for customers and fueling innovation. In the world of cybersecurity there is no shortage of competition, in fact cybersecurity is one of the most crowded and fast-growing areas of technology&#8230;. <a class="excerpt-read-more" href="strength-in-numbers-why-consider-open-source-cybersecurity-analytics/" title="Read Strength in Numbers: Why Consider Open Source Cybersecurity Analytics">Read more &raquo;</a>
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<h1 class="h2 entry-title"><a href="jupyter-notebooks-for-data-analysis" rel="bookmark" title="Jupyter Notebooks for Data Analysis">Jupyter Notebooks for Data Analysis</a></h1>
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<time class="updated entry-time" datetime="2016-09-22" itemprop="datePublished">
September 22, 2016
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Why Does Apache Spot Include iPython notebooks? The project team wants Apache Spot to be a versatile tool that can be used by anyone. This means that data scientists and developers need to be able to query and handle the source data to find all the information they need for their decision making. The&#8230; <a class="excerpt-read-more" href="jupyter-notebooks-for-data-analysis/" title="Read Jupyter Notebooks for Data Analysis">Read more &raquo;</a>
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<h1 class="h2 entry-title"><a href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" rel="bookmark" title="Apache Spot and Cybersecurity — Using NetFlows to Detect Threats to Critical Infrastructure">Apache Spot (Incubating) and Cybersecurity — Using NetFlows to Detect Threats to Critical Infrastructure</a></h1>
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<time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
August 8, 2016
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The “first” documented cybersecurity case was the worm replication, which was initiated by Robert T. Morris on November 2, 1988. Wow! Here we are in 2016, 28 years later, with viruses and worms giving way to Trojan horses and polymorphic code. Nowadays, we are also fighting against DDoS, phishing, spear phishing attacks, command and controls&#8230; <a class="excerpt-read-more" href="apache-spot-and-cybersecurity-using-netflows-to-detect-threats-to-critical-infrastructure/" title="Read Apache Spot and Cybersecurity — Using NetFlows to Detect Threats to Critical Infrastructure">Read more &raquo;</a>
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<h1 class="h2 entry-title"><a href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" rel="bookmark" title="How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">How Apache Spot (Incubating) Helps Create Well-Stocked Data Lakes and Catch Powerful Insights</a></h1>
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<time class="updated entry-time" datetime="2016-08-08" itemprop="datePublished">
August 8, 2016
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About four years ago, the era of the Big Data analytics began. Paired with advanced analytics, massive volumes of data can be culled to not only inform critical decisions, but also to simulate sophisticated “what if” scenarios that allow companies to gain competitive advantages by generating and predicting different scenarios. For example, a financial services&#8230; <a class="excerpt-read-more" href="how-apache-spot-helps-create-well-stocked-data-lakes-and-catch-powerful-insights/" title="Read How Apache Spot Helps Create Well-Stocked Data Lakes and Catch Powerful Insights">Read more &raquo;</a>
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<h1 class="h2 entry-title"><a href="apache-spot-3-most-asked-questions/" rel="bookmark" title="Apache Spot: Three Most-Asked Questions">Apache Spot (Incubating): Three Most-Asked Questions</a></h1>
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<time class="updated entry-time" datetime="2016-03-29" itemprop="datePublished">
March 29, 2016
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While this is not the first blog post about Apache Spot, it is the first one by a creator of the solution. As a security data scientist in Intel&#8217;s Data Center Group, I joined a small team to start thinking about solving really hard problems in cloud analytics. The team grew, and out of that&#8230; <a class="excerpt-read-more" href="apache-spot-3-most-asked-questions/" title="Read Apache Spot: Three Most-Asked Questions">Read more &raquo;</a>
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