InMemHealth Care Demo: Quality Measures.

The Centers for Medicare and Medicaid Services (CMS) defines Quality Measures as “tools that help us measure or quantify healthcare processes, outcomes, patient perceptions, and organizational structure and/or systems that are associated with the ability to provide high-quality health care and/or that relate to one or more quality goals for health care. These goals include: effective, safe, efficient, patient-centered, equitable, and timely care.”

This application presents an approach that a health system may want to take to visualize their data so that they can target the right areas for improvement. This data set contains 62.5 million quality records for 2.76 million patients and covers across 8 health systems, with 685 Practice Groups employing 5 thousand physicians. Launch Demo

InMemSAP Material Management: SAP Offload powered by Attunity

Attunity Replicate for SAP is a high-performance, automated and easy to use data replication solution that is optimized to deliver SAP application data in real-time for Big Data analytics. it moves the right SAP application data easily, securely and at scale to any major database, data warehouse or Hadoop, on premises or in the cloud. This solution builds on decades of leadership in enterprise data replication and SAP integration.

This application demonstates a direct load from SAP ECC into Cloudera. The data is loaded directly from SAP into HDFS and then turned into Impala tables that Qlik connects to and applies complex transforms to in adding business friendly terms and time series analytics capabilities.
Launch Demo

InMemOil and Gas Demo: Well Maintenance and Monitoring.

This demo leverages over 16 million IOT sensor and maint enance readings sourced from Kafka and Streamsets to create a Qlik app that allows deep analytics on well maintenance issues. With this app, there is the ability to drill down to a very granular level to see performance issues related with real world well production issues in Alberta, Canada.
Launch Demo

OnDemQlik Solr Demo: Qlik APIs + Solr building a webapp on demand.

What makes Qlik different than all other analytics tools is our powerful APIs. This webapp uses Solr to query the Enron email data set on any set of topics. That data is returned in JSON which Qlik parses, loads into the Qlik Engine (called QIX) and indexes. That indexed data is then consumed via APIs through a Bootstrap.JS interface to build, from scratch, a webapp that uses D3js and other web technologies to present the data, but without using any Qlik interfaces other than our APIs. This webapp is for searching the Enron email data set...

Launch Demo
DQImpala TPC-DS Direct Demo: Live query w/ Impala on Kudu

In this demo, Qlik uses our direct query capability to connect to Impala to run interactive queries with a TPC-DS data set stored in Kudu. The data is stored in Kudu as an alternative to parquet format. What's unique about Qlik is that even though the data is not being stored in memory initially, we still have the associative experience avaiable to the user. This capability executes queries in parallel against the Impala engine to acheive maximum performance.
Launch Demo

InMemZika Demo: Track the transmission and details of the Zika virus.

This demo is based on 20+ data sources that have been loaded into HDFS and then transformed into a pure in-memory Qlik app. The datasets that have been loaded into Cloudera are from a variety of sources including: CDC, World Health Organization, Twitter, Flight Stats data, Weather data, Texas hospital data, and other clinic sources. This highly visually stunning app showcases Qlik's ability to tell a powerful story with data.

Launch Demo
InMemMarket Basket Demo: Spark ML processed data + Impala on HDFS

Spark is one of the greatest Big Data advancements to appear on the scene since Hadoop. Qlik in this demo is going to leverage the power of Spark machine learning to process raw transactional data into "Market Baskets". A Market Basket is a categorization of similiar things sold in conjunction with each other, i.e. if I buy Product A, Product B,C and E are often sold with it, but not product D. This application merges the original Point of Sale data with the Spark machine learning processed data in-memory to analyze the Market Baskets.
Launch Demo

InMemUS Contract Spend: US Government Federal Spending Analysis

This app analyzes every US Government contract for 2011 - 2016 fiscal years. It includes over 18.7 million contracts with a total spend of over $2.6 trillion. Data was sourced from www.usaspending.gov and has been enriched with geo-spacial data for mapping capabilities. Displays key spending metrics such as total spend, # of contracts, # of vendors, and spend over time

Launch Demo
IMCloudera Search: Enron Demo: Solr data loaded via REST into Qlik

We have seen the power of the Qlik APIs using Solr data, but we have created a structured application to accomplish the same type of Enron email analysis - but using Qlik native components. This demo also fuses together stock data to profile email volumes versus stock price and trade volumes. This demo is a good example of the DAR (Dashboard, Analysis, Report) method Qlik uses to help users navigate applications and data.

Launch Demo
DQImpala Complex Data Types: Live queries of complex data types

This demo is entirely a technical demo showing how to use the more advanced special features of Cloudera Impala which is called Complex Types. Complex types (also referred to as nested types) let you represent multiple data values within a single row/column position. They differ from the familiar column types such as BIGINT and STRING, known as scalar types or primitive types, which represent a single data value within a given row/column position.

Launch Demo
DQTPC-DS Direct Demo: Live queries w/ Impala on Parquet

In this demo, Qlik uses our direct query capability to connect to Impala to run interactive queries with a TPC-DS data set stored in Kudu. The data is stored in Kudu as an alternative to parquet format. What's unique about Qlik is that even though the data is not being stored in memory initially, we still have the associative experience avaiable to the user. This capability executes queries in parallel against the Impala engine to acheive maximum performance.

Launch Demo
IMCloudera Manager Operation Dashboard via REST

This demo conencts to Cloudera Manager via 20+ REST API calls to collect operation metrics around our Cloudera Cluster performance. We are collecting operation stats for Hive, Yarn, Spark, Kudu, Kafka, Solr, and Impala. We are also collecting detailed query metrica and performance data for Impala. This application updates every hour to refresh the latest stats.

Launch Demo

InMem = In-Memory Applications | DQ = Direct Query Applications | OnDem = On-Demand Applications