webinar: fusion for business intelligence
TRANSCRIPT
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Fusion for Business Intelligence
Allan Syiek Senior Sales Engineer September 14, 2016
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Session Objec,ves
By the end of this session, you will: – Have a high level awareness of the variety of search and discovery funcFonality available
– Select the right product for a parFcular use case
– Know why this baby is so happy
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Agenda Ø The Beer and Diaper Legend Ø DIKW Pyramid Ø What is Enterprise Search Ø Indexing 101 Ø StaFsFcs vs. Data Mining vs. Machine Learning Ø What is Business Intelligence Ø Where does Fusion Fit?
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Parable of the Beer and the Diapers
Illustrates the difference between querying and data mining, already firmly enshrined in BI mythology
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The DIKW Pyramid
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What is Enterprise Search
Q. What do you do with a mountain of data located everywhere? A. Depends…. What do you need it for?
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• Crawling, Parsing, Indexing, Searching • Advanced Searches • Searching Structured Data • Searching Unstructured Data • Metadata • Ranking • Results • Access Control • UI • Tuning • ReporFng • Scale and Performance
Aspects of Enterprise Search
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Index Pipeline
Tika Parser Exclusion Filter Field Mapper HTML Transform Stage XML Transform Stage OpenNLP EnFty ExtracFon Gaze]eer ExtracFon Regular Expression AggregaFng Javascript (custom scripts) …and others…
Sear
ch C
olle
ctio
n
Sear
ch U
I
Search Fields/Parameters Facets Landing Pages Boost Documents Block Documents Security Trimming RecommendaFon BoosFng Rollup Aggregator Sub Query Javascript (custom scripts) …and others…
Doc
umen
tsQuery Pipeline
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Indexing 101
A system used to make finding informa,on easier.
Every word is converted into a wordID by using an in-‐memory hash table -‐-‐ the lexicon. Occurrences in the current document are translated into hit lists and are wri]en into the forward “barrels”. Inverted Barrels have been sorted.
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Indexing 101 -‐ Ranking
• Score Results for PresentaFon – Weighted by Term Frequency-‐Inverse Document Frequency (TF-‐IDF) – Clustering – Complex proprietary algorithms
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Indexing 101 -‐ Relevance
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Sta,s,cs vs. Data Mining vs. Machine Learning
– Sta,s,cs quan%fies numbers – Data Mining explains pa]erns – Machine Learning predicts with models – Ar,ficial Intelligence behaves and reasons
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What is Business Intelligence
• BI technologies provide historical, current and predicFve views of business operaFons
• Business intelligence is made up of an increasing number of components including: – MulFdimensional aggregaFon and allocaFon (OLAP– Online AnalyFcal Processing) – DenormalizaFon, tagging and standardizaFon (relaFonal database) – Real Fme reporFng with analyFcal alert – A method of interfacing with unstructured data sources (data mining) – Group consolidaFon, budgeFng and rolling forecasts – StaFsFcal inference and probabilisFc simulaFon – Key performance indicators opFmizaFon – Version control and process management – Open item management
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• Why Fusion for Log Analytics?
• Secure access to dashboards
• ETL of logs using Index pipelines
• Spark run analysis models for logs and leverage with ML index pipeline
• Time series index management
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Massive-‐scale log analyFcs
• Index billions of log events per day, real-time
• Recent event and historical analysis: Analyze logs over time: today, recent, past week, past 30 days, …
• Easy to use dashboards to visualize common
questions and allow for ad hoc analysis • Ability to scale linearly as business grows …
with sub-linear growth in costs!
• Easy to setup, easy to manage, easy to use
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• Signals & RecommendaFons
Fusion can capture, store, and aggregate signals from a variety of sources to drive predicFve search capabiliFes and conFnuous relevancy tuning
Signals can includeClicks and queries Add-‐to-‐cart and purchase behavior Geo-‐locaFon User behavior and preferences User history and past orders Device
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VisualizaFon & Insight with SILK
SILK Dashboards provide a rich visual interface for users to search, inspect and visualize event/log data Gives user the power to perform ad-hoc search and analysis on massive amounts of multi-structured and time series data. Real-time insights and trends for on-the-fly decision making using the most accurate and up-to-date data Users can share visualizations and dashboards
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REST API
Worker Worker Cluster Mgr.
Apache Spark
Shards Shards
Apache Solr
HDFS (O
pFon
al)
Shared Config Mgmt Leader ElecFon Load Balancing
ZK 1
Apache Zookeeper
ZK N
DATABASEWEBFILELOGSHADOOP CLOUD
Connectors
Alerting/Messaging
NLP
PipelinesBlob Storage
Scheduling
Recommenders/Signals
…
Core Services
Admin UI
SECURITY BUILT-IN
Lucidworks View
Where Does Fusion Fit?
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Learn more at -‐ lucenerevoluFon.org
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Thank You Q & A