InMemAnti-Money Laundering Demo: Pombar Bank
Demonstrates how Qlik, Cloudera and DataRobot can be integrated to provide a modern analytics stack for an anti-money laundering use case. The fictional PomBar Bank has just released an international payments system, powered by Ripple. They want to extend visibility of their AML/KYC system into their Ripple transaction data.”
Cloudera's Enterprise Data Hub provides the storage and infrastructure for a secure, governed anti-money laundering system, centralizing data across all legacy banking systems, as well as from Ripple's API. DataRobot - a highly automated platform for machine learning - is used to implement an anomaly detection routine, as part of PomBar's AML workflow. Qlik then provides an efficient end-user platform for monitoring, visualizing, and transforming that data. Launch Demo
OnDemCloudera Data Explorer
The Cloudera Data Explorer consumes metadata from Cloudera Navigator, Cloudera Manager, and Impala to enable the user to visually shop through the data lake for information they want to analyze in Qlik.
Business users can use Cloudera Data Explorer to access data stored anywhere in Cloudera and help guide them to create a Qlik application on the fly. Launch Demo
InMemCloudera Altus - Impala Analytic DB: TPCDS Demo
Cloudera Altus is a cloud service platform with services that enable you to use CDH to analyze and process data at scale within a public cloud infrastructure. It is designed to provision clusters quickly and to make it easy for you to build and run your data workloads in the cloud.
Altus works within the cloud service provider architecture. That framework provides an excellent foundation for Qlik Sense in a cloud based solution powered by Altus. This dashboard application is powered by Altus running a TPCDS data set on S3 and Impala as the query engine. Launch Demo
InMemCloudera Metadata Catalog - Impala, Navigator, Manager
Cloudera is rich in metadata useful for understanding the data behind the analytics visualized by Qlik. However, this metadata is somewhat scattered across different areas of the Cloudera ecosystem. In this application, Qlik is pulling valuable metadata from Cloudera Navigator and Cloudera Manager using REST API's. These API's give insight in query usage, query performance, and metadata tags using published API calls.
Combining this REST data with a series of looping SQL calls against Impala, we are able to associate database, table, and column statistics with the Navigator and Manager data. By combining this data, we are able to create a full understand of relevant Cloudera metadata that Qlik can analyze. This application also powers the selection criteria for the upcoming Cloudera Data Explorer. Launch Demo
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
OnDemBanking Demo: On-Demand Analytics
This demonstration showcases Qlik's ability to manage and consume large data sets in a governed environment using On-Demand Application Generation technology built into Qlik Sense. A user can browse summary information about banking trends and then drill down into the transaction "on-demand" to get the details.The user can only get the details once they have filtered down the amount of accounts to under 100 in this example. The resulting app is the users own persoanlized app to explore and create new content.
InMemSAP Sales & Distribution: 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 demonstrates 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.
InMemOil and Gas Demo: Well Maintenance and Monitoring.
This demo leverages over 16 million IOT sensor and maintenance 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.
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 (offline)
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.
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.
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 timeLaunch Demo
In-MemCloudera 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.