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Posted to commits@nifi.apache.org by al...@apache.org on 2017/11/15 17:27:10 UTC

svn commit: r1815344 - /nifi/site/trunk/powered-by-nifi.html

Author: alopresto
Date: Wed Nov 15 17:27:10 2017
New Revision: 1815344

URL: http://svn.apache.org/viewvc?rev=1815344&view=rev
Log:
Added Hastings Group and changed links to https. 

Modified:
    nifi/site/trunk/powered-by-nifi.html

Modified: nifi/site/trunk/powered-by-nifi.html
URL: http://svn.apache.org/viewvc/nifi/site/trunk/powered-by-nifi.html?rev=1815344&r1=1815343&r2=1815344&view=diff
==============================================================================
--- nifi/site/trunk/powered-by-nifi.html (original)
+++ nifi/site/trunk/powered-by-nifi.html Wed Nov 15 17:27:10 2017
@@ -129,20 +129,20 @@
                 <th>Industry</th>
                 <th>Summary</th>
             </tr>
-	    <tr>
-		<td><a href="http://micron.com">Micron</a></td>
+	        <tr>
+		        <td><a href="https://micron.com">Micron</a></td>
                 <td>Semiconductor Manufacturing</td>
                 <td>Micron's Enterprise Analytics and Data team uses NiFi to acquire worldwide manufacturing data and ingest it into symmetrical Global Data Warehouses.  This data is vaulted and exposed via data marts providing our data scientists and business partners a secured global view of our manufacturing processes.  For ingestion flows requiring higher performance transformations, we utilize the NiFi Site-to-Site protocol to seamlessly transfer processing to Spark jobs on our Hadoop clusters.  We have leveraged NiFi's REST API to automate the creation and monitoring of new ingestion pipelines which furthers our goal of providing a complete Global Data Warehouse.</td>
             </tr>
-	    <tr>
-		<td><a href="https://macquarietelecomgroup.com">Macquarie Telecom Group</a></td>
+	        <tr>
+		        <td><a href="https://macquarietelecomgroup.com">Macquarie Telecom Group</a></td>
                 <td>Cloud and Telecommunications</td>
                 <td>Uses Apache NiFi to securely and reliably transfer, transform, enrich and deliver billions of
                 individual events per day (i.e. security logs, system metrics, aggregated data sets, etc) across
                 multiple datacenters.</td>
             </tr>
             <tr>
-                <td><a href="http://www.dovestech.com">Dovestech</a></td>
+                <td><a href="https://www.dovestech.com">Dovestech</a></td>
                 <td>Cyber Security</td>
                 <td>Dovestech's cyber security visualization product, <a href="http://www.dovestech.com/threatpop">ThreatPop</a>, uses Apache NiFi to enrich and
                 normalize millions of cyber security related events into a central database
@@ -150,9 +150,9 @@
                 engine visualization technology.
             </tr>
             <tr>
-                <td><a href="http://www.flexilogix.com">Flexilogix</a></td>
+                <td><a href="https://www.flexilogix.com">Flexilogix</a></td>
                 <td>Big Data / IoT</td>
-		<td>Builds all data ingestion pipelines using NiFi. Have deployed NiFi clusters to ingest, transform and deliver to data analytics backends serving all purposes of data mediation both for realtime and batch jobs.</td>
+		        <td>Builds all data ingestion pipelines using NiFi. Have deployed NiFi clusters to ingest, transform and deliver to data analytics backends serving all purposes of data mediation both for realtime and batch jobs.</td>
             </tr>
             <tr>
                 <td><a href="https://www.payoff.com/">Payoff</a></td>
@@ -160,7 +160,7 @@
                 <td>NiFi primarily serves as our consumer between Kafka and HDFS. NiFi also provides schema validation for event streams while enabling us to modify and republish secure event streams for general use. NiFi extracts and standardizes large datasets from third parties between various sources including HDFS/s3/Kafka/sftp.</td>
             </tr>
             <tr>
-                <td><a href="http://www.onyxpoint.com">Onyx Point</a></td>
+                <td><a href="https://www.onyxpoint.com">Onyx Point</a></td>
                 <td>Commercial/Federal Consulting</td>
                 <td>Design large scale NIFI clusters for high volume ingest/egress and provide day to day operational support and maintenance.</td>
             </tr>
@@ -185,10 +185,15 @@
             	<td>Think Big's open-source data lake management platform <a href="http://kylo.io">Kylo</a> offers a turn-key, enterprise-ready data lake solution that integrates best practices around metadata management, governance, and security gleaned from Think Big's 150+ big data implementation projects. Kylo uses Apache NiFi as the underlying scheduler and orchestration engine, along with other technologies like Apache Hadoop and Apache Spark.</td>
             </tr>
             <tr>
-                <td><a href="http://www.hashmapinc.com/">Hashmap, Inc.</a></td>
+                <td><a href="https://www.hashmapinc.com/">Hashmap, Inc.</a></td>
                 <td>Big Data / IoT</td>
                 <td>Hashmap uses Apache NiFi to securely collect, transmit, and transform data for ingest and delivery into our IoT / Time Series Accelerator platform, allowing for outcome-based, real time analytics and visualization of oil & gas, utilities, manufacturing, industrial, retail, pharma, and process control data. Additionally, we are creating a catalog of open source, ready-to-run, industry specific NiFi processors and controller services for protocols like OPC-UA, ETP, WITSML, LAS, and many others.</td>
             </tr>
+            <tr>
+                <td><a href="https://www.hastingsdirect.com/">Hastings Group</a></td>
+                <td>Insurance</td>
+                <td>Hastings Group is a fast growing, agile, digitally focused general insurance provider providing services to the UK car, van, bike and home insurance market. We have strong relationships with all major price comparison websites (PCWs) and utilise Apache NiFi to process and ingest millions of items of data.</td>
+            </tr>
         </table>
     </div>
 </div>