SlideShare a Scribd company logo
Data Analysis and Visualization
with MongoDB
Alexander C. S. Hendorf
@hendorf
MongoDB World 2016, NYC
Alexander C. S. Hendorf
CTO Königsweg GmbH
mongoDB master 2016, MUG Leader
EuroPython organizer + program chair
Speaker EuroPython, mongoDB days, CEBIT, PyCon It, PyData…
Hobbies: see above
@hendorf
#15
180+sessions
20free
trainings
interactive
sessions
panels
open
spaces
social
event
5dtalks &
trainings
2dsprints
beginners’ day
17th - 24th of July
@EuroPython
Data analysis and visualization with mongo db [mongodb world 2016]
2003 2012 2016
2003 2012 2016
2003 2012 2016
2003 2012 2016
Apple launches the iTunes music store in the U.S.
2003 2012 2016
Apple launches the iTunes music store in the U.S.
14
77
122
2x
122
global coverage + Apple Music
x 10 Genres
x 3 Single, Album,
Video
Data analysis and visualization with mongo db [mongodb world 2016]
Data analysis and visualization with mongo db [mongodb world 2016]
RDBS Data Lake
mongoDB Data Lake
Aggregation
Framework
Data analysis and visualization with mongo db [mongodb world 2016]
Data analysis and visualization with mongo db [mongodb world 2016]
{'_id': ObjectId('56deffde0947000f05fc415a'),
'adamIds': [
'1067854407',
'1063750649',
'1064007468',
'1066300693',
...
'271232254',
'453857235',
'377045644'
],
'kinds': {'album': True},
'title': 'Top Albums’
},
'discovered': 1457447797.81184,
'store-id': ‚143444‘,
'url': 'https://itunes…/viewTop?id=27740&genreId=50'
}
position = rank in charts
array
unix timestamp
1
2
3
200
chart id
'adamIds': ['1067854407',
'1063750649',
'1064007468',
'1066300693',
'296867433',
'956751167',
'328069028',
'505586080',
'676328847',
'642644496',
'271232254',
'453857235',
'377045644'],
'discovered': 1457447797
'adamIds': ['1067854407',
'453857235',
'1063750649',
'1066300693',
'296867433',
'328069028',
'292372676',
'505586080',
'676328847',
'642644496',
'956751167',
'271232254',
'544816699'],
'discovered': 1457447836
'adamIds': ['1067854407',
'1063750649',
'1064007468',
'1066300693',
'296867433',
'956751167',
'328069028',
'505586080',
'676328847',
'642644496',
'271232254',
'453857235',
'377045644'],
'discovered': 1457447797
'adamIds': ['1067854407',
'453857235',
'1063750649',
'1066300693',
'296867433',
'328069028',
'292372676',
'505586080',
'676328847',
'642644496',
'956751167',
'271232254',
'544816699'],
'discovered': 1457447836
1
200
100
rank
documents / time
pipeline = [
{"$match": {
"discovered": {$gte: 1457447797, $lte: 1457447836}
"url": "http://the/url/is/a/identifier/the/chart/"},
{"$unwind": {"$adamId"}},
{"$group": …
"$push: ""$adamId"}
]
pipeline1 = [{"$match": {…}}, 

{"$project": {"products": "$chart.adamIds", "discovered": "$downloadinfo.discovered"}},
# unwind with numbering
{"$unwind":
{ "path": "$products", "includeArrayIndex": "arrayIndex" }},
{"$project":
{"product": "$products",
# arrayIndex attribute was added by $unwind, is 0-indexed
"rank": {"$add": ["$arrayIndex", 1 ]},
"discovered": 1,
# any '_id' attribute must be unique for storing, rename
"_id": 0, "origin_id": "$_id"}},
{"$sort": {"origin_id": -1}},
# save as new collection
{"$out": "individual_movements"}
]
1
'products': ['1067854407',
'1063750649',
...
'642644496',
'377045644'],
'discovered': 1457447797
[ {'_id': ObjectId('572c69bc8651fa448821083b'),
'discovered': 1441110721.19208,
'origin_id': ObjectId('55e59b260947007aef84dccb'),
'rank': 1,
'product': '1032438740'},
{'_id': ObjectId('572c69bc8651fa448821083c'),
'discovered': 1441110721.19208,
'origin_id': ObjectId('55e59b260947007aef84dccb'),
'rank': 2,
'product': '976241375'}, …
]
pipeline2 = [
{"$group": {"_id": "$origin_id",
"discovered": {"$first": "$discovered"}}},
{"$project": {"discovered": 1, "_id": 1}},
{"$out": "x_axis"}
]
2
[{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'discovered': 1435710159.830053},
{'_id': ObjectId('5594ae5f09470044a56f1c61'),
'discovered': 1435807294.457157},
{'_id': ObjectId('5594bcaac419ab6d280b740e'),
'discovered': 1435810952.364217}]
pipeline3 = [
{"$lookup": {"from": "individual_movements",
"localField": "_id",
"foreignField": "origin_id",
"as": "values"}},
{"$unwind": "$values"},
{"$project": {"product": "$values.product",
"rank": "$values.rank",
"discovered": 1}}
]
3
Data analysis and visualization with mongo db [mongodb world 2016]
x_axis collection: documents / time
1
200
100
individual_movements: rank
x_axis collection: documents / time
[{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'discovered': 1435710159.830053,
'rank': 1,
'product': '1000697870'},
{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'discovered': 1435710159.830053,
'rank': 2,
'product': '986637877'},
{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'discovered': 1435710159.830053,
'rank': 3,
'product': '995987630'},…]
Data analysis and visualization with mongo db [mongodb world 2016]
Data Scientists?
Data analysis and visualization with mongo db [mongodb world 2016]
Data analysis and visualization with mongo db [mongodb world 2016]
Data Scientists!
• Grant	access	with	the	built	in	

role	management	
• Data	scientists	can	analyse	the	data	
with	typical	tools	as	Pandas,	R,	etc…	
• easy	as	a	cake	with	VIEWs	coming	in	
3.4	:-)
Data
Visualization!
0
25
50
75
100
April May June July
Analysts?
BI Connector
Data analysis and visualization with mongo db [mongodb world 2016]
{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'rank': 0,
'product': '1000697870':
'abc': ["a", "b", "c"]
}
schema:

- db: mydatabase

tables:

- table: my_mongodb_collection

collection: my_mongodb_collection

pipeline: []

columns:

- Name: _id

MongoType: bson.ObjectId

SqlName: _id

SqlType: varchar

- Name: rank

MongoType: int

SqlName: rank

SqlType: numeric

- Name: product

MongoType: string

SqlName: product

SqlType: varchar

…

{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'rank': 0,
'product': '1000697870':
'abc': ["a", "b", "c"]
}
SqlType: varchar

- Name: rank

MongoType: int

SqlName: rank

SqlType: numeric

- Name: product

MongoType: string

SqlName: product

SqlType: varchar

…

{'_id': ObjectId('559332e6c419ab6d8b0738f9'),
'rank': 0,
'product': '1000697870':
'abc': ["a", "b", "c"]
}
- table: my_mongodb_collection_abc

collection: my_mongodb_collection

pipeline:

- $unwind:

includeArrayIndex: abc

path: $abc

columns:

- Name: abc

MongoType: string

SqlName: abc

…
mongobiuser create user mongodb://localhost:27017/myDB
# create a user account
mongodrdl --host localhost -d myDB -o schema.drdl
# create the schema
mongobischema import user schema.drdl
# load the schema
BI Connector
Data analysis and visualization with mongo db [mongodb world 2016]
Data analysis and visualization with mongo db [mongodb world 2016]
Analysts!
BI	Connector	
• access	mongoDB	from	BI	tools	
• mock-up	of	RDBS	
• BI	user	accounts
Data analysis and visualization with mongo db [mongodb world 2016]
Data analysis and visualization with mongo db [mongodb world 2016]
Alexander C. S. Hendorf
@hendorf

More Related Content

What's hot

The Ring programming language version 1.9 book - Part 53 of 210
The Ring programming language version 1.9 book - Part 53 of 210The Ring programming language version 1.9 book - Part 53 of 210
The Ring programming language version 1.9 book - Part 53 of 210
Mahmoud Samir Fayed
 
Fixing Web Data in Production
Fixing Web Data in ProductionFixing Web Data in Production
Fixing Web Data in Production
Aaron Knight
 
NoSQL in SQL - Lior Altarescu
NoSQL in SQL - Lior Altarescu NoSQL in SQL - Lior Altarescu
NoSQL in SQL - Lior Altarescu
Wix Engineering
 
Working with NoSQL in a SQL Database (XDevApi)
Working with NoSQL in a SQL Database (XDevApi)Working with NoSQL in a SQL Database (XDevApi)
Working with NoSQL in a SQL Database (XDevApi)
Lior Altarescu
 
Getting Started with MongoDB and NodeJS
Getting Started with MongoDB and NodeJSGetting Started with MongoDB and NodeJS
Getting Started with MongoDB and NodeJS
MongoDB
 
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
MongoSF
 
The Ring programming language version 1.5 book - Part 8 of 31
The Ring programming language version 1.5 book - Part 8 of 31The Ring programming language version 1.5 book - Part 8 of 31
The Ring programming language version 1.5 book - Part 8 of 31
Mahmoud Samir Fayed
 
Mythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDBMythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDB
MongoDB
 
Using Arbor/ RGraph JS libaries for Data Visualisation
Using Arbor/ RGraph JS libaries for Data VisualisationUsing Arbor/ RGraph JS libaries for Data Visualisation
Using Arbor/ RGraph JS libaries for Data Visualisation
Alex Hardman
 
Git as NoSQL
Git as NoSQLGit as NoSQL
Git as NoSQL
Somkiat Puisungnoen
 
MongoDB With Style
MongoDB With StyleMongoDB With Style
MongoDB With Style
Gabriele Lana
 
Green dao
Green daoGreen dao
Green dao
彥彬 洪
 
The Ring programming language version 1.7 book - Part 47 of 196
The Ring programming language version 1.7 book - Part 47 of 196The Ring programming language version 1.7 book - Part 47 of 196
The Ring programming language version 1.7 book - Part 47 of 196
Mahmoud Samir Fayed
 
Android mix Java and C++
Android mix Java and C++Android mix Java and C++
Android mix Java and C++
Maksym Davydov
 
MongoDB Performance Debugging
MongoDB Performance DebuggingMongoDB Performance Debugging
MongoDB Performance Debugging
MongoDB
 
The Ring programming language version 1.10 book - Part 79 of 212
The Ring programming language version 1.10 book - Part 79 of 212The Ring programming language version 1.10 book - Part 79 of 212
The Ring programming language version 1.10 book - Part 79 of 212
Mahmoud Samir Fayed
 
Windows Server 2012 Active Directory Recovery
Windows Server 2012 Active Directory RecoveryWindows Server 2012 Active Directory Recovery
Windows Server 2012 Active Directory Recovery
Serhad MAKBULOĞLU, MBA
 
Geospatial Enhancements in MongoDB 2.4
Geospatial Enhancements in MongoDB 2.4Geospatial Enhancements in MongoDB 2.4
Geospatial Enhancements in MongoDB 2.4
MongoDB
 
The Ring programming language version 1.4.1 book - Part 12 of 31
The Ring programming language version 1.4.1 book - Part 12 of 31The Ring programming language version 1.4.1 book - Part 12 of 31
The Ring programming language version 1.4.1 book - Part 12 of 31
Mahmoud Samir Fayed
 
Hibernate online training
Hibernate online trainingHibernate online training
Hibernate online training
QUONTRASOLUTIONS
 

What's hot (20)

The Ring programming language version 1.9 book - Part 53 of 210
The Ring programming language version 1.9 book - Part 53 of 210The Ring programming language version 1.9 book - Part 53 of 210
The Ring programming language version 1.9 book - Part 53 of 210
 
Fixing Web Data in Production
Fixing Web Data in ProductionFixing Web Data in Production
Fixing Web Data in Production
 
NoSQL in SQL - Lior Altarescu
NoSQL in SQL - Lior Altarescu NoSQL in SQL - Lior Altarescu
NoSQL in SQL - Lior Altarescu
 
Working with NoSQL in a SQL Database (XDevApi)
Working with NoSQL in a SQL Database (XDevApi)Working with NoSQL in a SQL Database (XDevApi)
Working with NoSQL in a SQL Database (XDevApi)
 
Getting Started with MongoDB and NodeJS
Getting Started with MongoDB and NodeJSGetting Started with MongoDB and NodeJS
Getting Started with MongoDB and NodeJS
 
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
Map/reduce, geospatial indexing, and other cool features (Kristina Chodorow)
 
The Ring programming language version 1.5 book - Part 8 of 31
The Ring programming language version 1.5 book - Part 8 of 31The Ring programming language version 1.5 book - Part 8 of 31
The Ring programming language version 1.5 book - Part 8 of 31
 
Mythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDBMythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDB
 
Using Arbor/ RGraph JS libaries for Data Visualisation
Using Arbor/ RGraph JS libaries for Data VisualisationUsing Arbor/ RGraph JS libaries for Data Visualisation
Using Arbor/ RGraph JS libaries for Data Visualisation
 
Git as NoSQL
Git as NoSQLGit as NoSQL
Git as NoSQL
 
MongoDB With Style
MongoDB With StyleMongoDB With Style
MongoDB With Style
 
Green dao
Green daoGreen dao
Green dao
 
The Ring programming language version 1.7 book - Part 47 of 196
The Ring programming language version 1.7 book - Part 47 of 196The Ring programming language version 1.7 book - Part 47 of 196
The Ring programming language version 1.7 book - Part 47 of 196
 
Android mix Java and C++
Android mix Java and C++Android mix Java and C++
Android mix Java and C++
 
MongoDB Performance Debugging
MongoDB Performance DebuggingMongoDB Performance Debugging
MongoDB Performance Debugging
 
The Ring programming language version 1.10 book - Part 79 of 212
The Ring programming language version 1.10 book - Part 79 of 212The Ring programming language version 1.10 book - Part 79 of 212
The Ring programming language version 1.10 book - Part 79 of 212
 
Windows Server 2012 Active Directory Recovery
Windows Server 2012 Active Directory RecoveryWindows Server 2012 Active Directory Recovery
Windows Server 2012 Active Directory Recovery
 
Geospatial Enhancements in MongoDB 2.4
Geospatial Enhancements in MongoDB 2.4Geospatial Enhancements in MongoDB 2.4
Geospatial Enhancements in MongoDB 2.4
 
The Ring programming language version 1.4.1 book - Part 12 of 31
The Ring programming language version 1.4.1 book - Part 12 of 31The Ring programming language version 1.4.1 book - Part 12 of 31
The Ring programming language version 1.4.1 book - Part 12 of 31
 
Hibernate online training
Hibernate online trainingHibernate online training
Hibernate online training
 

Viewers also liked

Biologia
BiologiaBiologia
MongoDB World 2016: MongoDB + Google Cloud
MongoDB World 2016: MongoDB + Google CloudMongoDB World 2016: MongoDB + Google Cloud
MongoDB World 2016: MongoDB + Google Cloud
MongoDB
 
MongoDB World 2016: Number Crush
MongoDB World 2016: Number CrushMongoDB World 2016: Number Crush
MongoDB World 2016: Number Crush
MongoDB
 
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
MongoDB
 
MongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
MongoDB World 2016: Get MEAN and Lean with MongoDB and KubernetesMongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
MongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
MongoDB
 
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
Amazon Web Services
 
MongoDB World 2016 : Advanced Aggregation
MongoDB World 2016 : Advanced AggregationMongoDB World 2016 : Advanced Aggregation
MongoDB World 2016 : Advanced Aggregation
Joe Drumgoole
 
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right WayMongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
MongoDB
 
MongoDB World 2016: The Best IoT Analytics with MongoDB
MongoDB World 2016: The Best IoT Analytics with MongoDBMongoDB World 2016: The Best IoT Analytics with MongoDB
MongoDB World 2016: The Best IoT Analytics with MongoDB
MongoDB
 
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho
 
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
NoSQLmatters
 
Data Mashups for Analytics
Data Mashups for AnalyticsData Mashups for Analytics
Data Mashups for Analytics
Pentaho
 
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
Amazon Web Services
 
MongoDB World 2016: Scaling MongoDB with Docker and cGroups
MongoDB World 2016: Scaling MongoDB with Docker and cGroupsMongoDB World 2016: Scaling MongoDB with Docker and cGroups
MongoDB World 2016: Scaling MongoDB with Docker and cGroups
MongoDB
 

Viewers also liked (14)

Biologia
BiologiaBiologia
Biologia
 
MongoDB World 2016: MongoDB + Google Cloud
MongoDB World 2016: MongoDB + Google CloudMongoDB World 2016: MongoDB + Google Cloud
MongoDB World 2016: MongoDB + Google Cloud
 
MongoDB World 2016: Number Crush
MongoDB World 2016: Number CrushMongoDB World 2016: Number Crush
MongoDB World 2016: Number Crush
 
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
MongoDB World 2016: From the Polls to the Trolls: Seeing What the World Think...
 
MongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
MongoDB World 2016: Get MEAN and Lean with MongoDB and KubernetesMongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
MongoDB World 2016: Get MEAN and Lean with MongoDB and Kubernetes
 
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
AWS January 2016 Webinar Series - Building Smart Applications with Amazon Mac...
 
MongoDB World 2016 : Advanced Aggregation
MongoDB World 2016 : Advanced AggregationMongoDB World 2016 : Advanced Aggregation
MongoDB World 2016 : Advanced Aggregation
 
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right WayMongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
MongoDB Europe 2016 - ETL for Pros – Getting Data Into MongoDB The Right Way
 
MongoDB World 2016: The Best IoT Analytics with MongoDB
MongoDB World 2016: The Best IoT Analytics with MongoDBMongoDB World 2016: The Best IoT Analytics with MongoDB
MongoDB World 2016: The Best IoT Analytics with MongoDB
 
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
Pentaho Analytics for MongoDB - presentation from MongoDB World 2014
 
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
Dan Sullivan - Data Analytics and Text Mining with MongoDB - NoSQL matters Du...
 
Data Mashups for Analytics
Data Mashups for AnalyticsData Mashups for Analytics
Data Mashups for Analytics
 
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
AWS re:Invent 2016: Understanding IoT Data: How to Leverage Amazon Kinesis in...
 
MongoDB World 2016: Scaling MongoDB with Docker and cGroups
MongoDB World 2016: Scaling MongoDB with Docker and cGroupsMongoDB World 2016: Scaling MongoDB with Docker and cGroups
MongoDB World 2016: Scaling MongoDB with Docker and cGroups
 

Similar to Data analysis and visualization with mongo db [mongodb world 2016]

Data mangling with mongo db the right way [pyconit 2016]
Data mangling with mongo db the right way [pyconit 2016]Data mangling with mongo db the right way [pyconit 2016]
Data mangling with mongo db the right way [pyconit 2016]
Alexander Hendorf
 
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDBMongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
MongoDB
 
NoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
NoSQL oder: Freiheit ist nicht schmerzfrei - IT TageNoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
NoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
Alexander Hendorf
 
Data Mangling with mongoDB the Right Way [PyData London] 2016]
Data Mangling with mongoDB the Right Way [PyData London] 2016]Data Mangling with mongoDB the Right Way [PyData London] 2016]
Data Mangling with mongoDB the Right Way [PyData London] 2016]
Alexander Hendorf
 
JSON and Swift, Still A Better Love Story Than Twilight
JSON and Swift, Still A Better Love Story Than TwilightJSON and Swift, Still A Better Love Story Than Twilight
JSON and Swift, Still A Better Love Story Than Twilight
Donny Wals
 
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스 AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
Amazon Web Services Korea
 
Lighting talk neo4j fosdem 2011
Lighting talk neo4j fosdem 2011Lighting talk neo4j fosdem 2011
Lighting talk neo4j fosdem 2011
Jordi Valverde
 
Building and Scaling the Internet of Things with MongoDB at Vivint
Building and Scaling the Internet of Things with MongoDB at Vivint Building and Scaling the Internet of Things with MongoDB at Vivint
Building and Scaling the Internet of Things with MongoDB at Vivint
MongoDB
 
Operational Intelligence with MongoDB Webinar
Operational Intelligence with MongoDB WebinarOperational Intelligence with MongoDB Webinar
Operational Intelligence with MongoDB Webinar
MongoDB
 
Back to Basics, webinar 2: La tua prima applicazione MongoDB
Back to Basics, webinar 2: La tua prima applicazione MongoDBBack to Basics, webinar 2: La tua prima applicazione MongoDB
Back to Basics, webinar 2: La tua prima applicazione MongoDB
MongoDB
 
How I hacked the Google Daydream controller
How I hacked the Google Daydream controllerHow I hacked the Google Daydream controller
How I hacked the Google Daydream controller
Matteo Pisani
 
MongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
MongoDB Days Silicon Valley: MongoDB and the Hadoop ConnectorMongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
MongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
MongoDB
 
He stopped using for/while loops, you won't believe what happened next!
He stopped using for/while loops, you won't believe what happened next!He stopped using for/while loops, you won't believe what happened next!
He stopped using for/while loops, you won't believe what happened next!
François-Guillaume Ribreau
 
Conceptos básicos. Seminario web 5: Introducción a Aggregation Framework
Conceptos básicos. Seminario web 5: Introducción a Aggregation FrameworkConceptos básicos. Seminario web 5: Introducción a Aggregation Framework
Conceptos básicos. Seminario web 5: Introducción a Aggregation Framework
MongoDB
 
What's new in Vaadin 8, how do you upgrade, and what's next?
What's new in Vaadin 8, how do you upgrade, and what's next?What's new in Vaadin 8, how do you upgrade, and what's next?
What's new in Vaadin 8, how do you upgrade, and what's next?
Marcus Hellberg
 
A look inside the European Covid Green Certificate - Rust Dublin
A look inside the European Covid Green Certificate - Rust DublinA look inside the European Covid Green Certificate - Rust Dublin
A look inside the European Covid Green Certificate - Rust Dublin
Luciano Mammino
 
How to leverage what's new in MongoDB 3.6
How to leverage what's new in MongoDB 3.6How to leverage what's new in MongoDB 3.6
How to leverage what's new in MongoDB 3.6
Maxime Beugnet
 
Mongodb Meetup Group 052012
Mongodb Meetup Group 052012Mongodb Meetup Group 052012
Mongodb Meetup Group 052012
scrazzl
 
The Rough Guide to MongoDB
The Rough Guide to MongoDBThe Rough Guide to MongoDB
The Rough Guide to MongoDB
Simeon Simeonov
 
2013-03-23 - NoSQL Spartakiade
2013-03-23 - NoSQL Spartakiade2013-03-23 - NoSQL Spartakiade
2013-03-23 - NoSQL Spartakiade
Johannes Hoppe
 

Similar to Data analysis and visualization with mongo db [mongodb world 2016] (20)

Data mangling with mongo db the right way [pyconit 2016]
Data mangling with mongo db the right way [pyconit 2016]Data mangling with mongo db the right way [pyconit 2016]
Data mangling with mongo db the right way [pyconit 2016]
 
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDBMongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
MongoDB Days Silicon Valley: Data Analysis and MapReduce with MongoDB
 
NoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
NoSQL oder: Freiheit ist nicht schmerzfrei - IT TageNoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
NoSQL oder: Freiheit ist nicht schmerzfrei - IT Tage
 
Data Mangling with mongoDB the Right Way [PyData London] 2016]
Data Mangling with mongoDB the Right Way [PyData London] 2016]Data Mangling with mongoDB the Right Way [PyData London] 2016]
Data Mangling with mongoDB the Right Way [PyData London] 2016]
 
JSON and Swift, Still A Better Love Story Than Twilight
JSON and Swift, Still A Better Love Story Than TwilightJSON and Swift, Still A Better Love Story Than Twilight
JSON and Swift, Still A Better Love Story Than Twilight
 
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스 AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
AWS 9월 웨비나 | AWS Lambda@Edge를 통한 엣지 컴퓨팅 서비스
 
Lighting talk neo4j fosdem 2011
Lighting talk neo4j fosdem 2011Lighting talk neo4j fosdem 2011
Lighting talk neo4j fosdem 2011
 
Building and Scaling the Internet of Things with MongoDB at Vivint
Building and Scaling the Internet of Things with MongoDB at Vivint Building and Scaling the Internet of Things with MongoDB at Vivint
Building and Scaling the Internet of Things with MongoDB at Vivint
 
Operational Intelligence with MongoDB Webinar
Operational Intelligence with MongoDB WebinarOperational Intelligence with MongoDB Webinar
Operational Intelligence with MongoDB Webinar
 
Back to Basics, webinar 2: La tua prima applicazione MongoDB
Back to Basics, webinar 2: La tua prima applicazione MongoDBBack to Basics, webinar 2: La tua prima applicazione MongoDB
Back to Basics, webinar 2: La tua prima applicazione MongoDB
 
How I hacked the Google Daydream controller
How I hacked the Google Daydream controllerHow I hacked the Google Daydream controller
How I hacked the Google Daydream controller
 
MongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
MongoDB Days Silicon Valley: MongoDB and the Hadoop ConnectorMongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
MongoDB Days Silicon Valley: MongoDB and the Hadoop Connector
 
He stopped using for/while loops, you won't believe what happened next!
He stopped using for/while loops, you won't believe what happened next!He stopped using for/while loops, you won't believe what happened next!
He stopped using for/while loops, you won't believe what happened next!
 
Conceptos básicos. Seminario web 5: Introducción a Aggregation Framework
Conceptos básicos. Seminario web 5: Introducción a Aggregation FrameworkConceptos básicos. Seminario web 5: Introducción a Aggregation Framework
Conceptos básicos. Seminario web 5: Introducción a Aggregation Framework
 
What's new in Vaadin 8, how do you upgrade, and what's next?
What's new in Vaadin 8, how do you upgrade, and what's next?What's new in Vaadin 8, how do you upgrade, and what's next?
What's new in Vaadin 8, how do you upgrade, and what's next?
 
A look inside the European Covid Green Certificate - Rust Dublin
A look inside the European Covid Green Certificate - Rust DublinA look inside the European Covid Green Certificate - Rust Dublin
A look inside the European Covid Green Certificate - Rust Dublin
 
How to leverage what's new in MongoDB 3.6
How to leverage what's new in MongoDB 3.6How to leverage what's new in MongoDB 3.6
How to leverage what's new in MongoDB 3.6
 
Mongodb Meetup Group 052012
Mongodb Meetup Group 052012Mongodb Meetup Group 052012
Mongodb Meetup Group 052012
 
The Rough Guide to MongoDB
The Rough Guide to MongoDBThe Rough Guide to MongoDB
The Rough Guide to MongoDB
 
2013-03-23 - NoSQL Spartakiade
2013-03-23 - NoSQL Spartakiade2013-03-23 - NoSQL Spartakiade
2013-03-23 - NoSQL Spartakiade
 

More from Alexander Hendorf

Deep Learning for Fun and Profit [PyConDE 2018]
Deep Learning for Fun and Profit [PyConDE 2018]Deep Learning for Fun and Profit [PyConDE 2018]
Deep Learning for Fun and Profit [PyConDE 2018]
Alexander Hendorf
 
Databases for Data Science
Databases for Data ScienceDatabases for Data Science
Databases for Data Science
Alexander Hendorf
 
Agile Datenanalsyse - der schnelle Weg zum Mehrwert
Agile Datenanalsyse - der schnelle Weg zum MehrwertAgile Datenanalsyse - der schnelle Weg zum Mehrwert
Agile Datenanalsyse - der schnelle Weg zum Mehrwert
Alexander Hendorf
 
Einführung Datenanalyse mit Pandas [data2day]
Einführung Datenanalyse mit Pandas [data2day]Einführung Datenanalyse mit Pandas [data2day]
Einführung Datenanalyse mit Pandas [data2day]
Alexander Hendorf
 
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
Alexander Hendorf
 
Introduction to Pandas and Time Series Analysis [PyCon DE]
Introduction to Pandas and Time Series Analysis [PyCon DE]Introduction to Pandas and Time Series Analysis [PyCon DE]
Introduction to Pandas and Time Series Analysis [PyCon DE]
Alexander Hendorf
 
Introduction to Data Analtics with Pandas [PyCon Cz]
Introduction to Data Analtics with Pandas [PyCon Cz]Introduction to Data Analtics with Pandas [PyCon Cz]
Introduction to Data Analtics with Pandas [PyCon Cz]
Alexander Hendorf
 
Neat Analytics with Pandas 4 3 [PyParis]
Neat Analytics with Pandas 4 3 [PyParis]Neat Analytics with Pandas 4 3 [PyParis]
Neat Analytics with Pandas 4 3 [PyParis]
Alexander Hendorf
 
Time travel and time series analysis with pandas + statsmodels
Time travel and time series analysis with pandas + statsmodelsTime travel and time series analysis with pandas + statsmodels
Time travel and time series analysis with pandas + statsmodels
Alexander Hendorf
 

More from Alexander Hendorf (9)

Deep Learning for Fun and Profit [PyConDE 2018]
Deep Learning for Fun and Profit [PyConDE 2018]Deep Learning for Fun and Profit [PyConDE 2018]
Deep Learning for Fun and Profit [PyConDE 2018]
 
Databases for Data Science
Databases for Data ScienceDatabases for Data Science
Databases for Data Science
 
Agile Datenanalsyse - der schnelle Weg zum Mehrwert
Agile Datenanalsyse - der schnelle Weg zum MehrwertAgile Datenanalsyse - der schnelle Weg zum Mehrwert
Agile Datenanalsyse - der schnelle Weg zum Mehrwert
 
Einführung Datenanalyse mit Pandas [data2day]
Einführung Datenanalyse mit Pandas [data2day]Einführung Datenanalyse mit Pandas [data2day]
Einführung Datenanalyse mit Pandas [data2day]
 
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
Introduction to Pandas and Time Series Analysis [Budapest BI Forum]
 
Introduction to Pandas and Time Series Analysis [PyCon DE]
Introduction to Pandas and Time Series Analysis [PyCon DE]Introduction to Pandas and Time Series Analysis [PyCon DE]
Introduction to Pandas and Time Series Analysis [PyCon DE]
 
Introduction to Data Analtics with Pandas [PyCon Cz]
Introduction to Data Analtics with Pandas [PyCon Cz]Introduction to Data Analtics with Pandas [PyCon Cz]
Introduction to Data Analtics with Pandas [PyCon Cz]
 
Neat Analytics with Pandas 4 3 [PyParis]
Neat Analytics with Pandas 4 3 [PyParis]Neat Analytics with Pandas 4 3 [PyParis]
Neat Analytics with Pandas 4 3 [PyParis]
 
Time travel and time series analysis with pandas + statsmodels
Time travel and time series analysis with pandas + statsmodelsTime travel and time series analysis with pandas + statsmodels
Time travel and time series analysis with pandas + statsmodels
 

Recently uploaded

Potential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriatePotential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriate
huseindihon
 
the unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithmthe unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithm
huseindihon
 
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
sharonblush
 
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).docbai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
PhngThLmHnh
 
ch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ssch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ss
MinThetLwin1
 
NPS_Presentation_V3.pptx it is regarding National pension scheme
NPS_Presentation_V3.pptx it is regarding National pension schemeNPS_Presentation_V3.pptx it is regarding National pension scheme
NPS_Presentation_V3.pptx it is regarding National pension scheme
ASISHSABAT3
 
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
tanupasswan6
 
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
tanupasswan6
 
ISBP 821 - UCP 600 - ed).pdf banking standards
ISBP 821 - UCP 600 - ed).pdf banking standardsISBP 821 - UCP 600 - ed).pdf banking standards
ISBP 821 - UCP 600 - ed).pdf banking standards
DevanshuAnada1
 
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
vrvipin164
 
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
44annissa
 
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy DsouzaOpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
OpenMetadata
 
transgenders community data in india by govt
transgenders community data in india by govttransgenders community data in india by govt
transgenders community data in india by govt
palanisamyiiiier
 
🚂🚘 Premium Girls Call Nashik 🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
🚂🚘 Premium Girls Call Nashik  🛵🚡000XX00000 💃 Choose Best And Top Girl Service...🚂🚘 Premium Girls Call Nashik  🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
🚂🚘 Premium Girls Call Nashik 🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
kuldeepsharmaks8120
 
Introduction to the Red Hat Portfolio.pdf
Introduction to the Red Hat Portfolio.pdfIntroduction to the Red Hat Portfolio.pdf
Introduction to the Red Hat Portfolio.pdf
kihus38
 
CHAPTER-1-Introduction-to-Marketing.pptx
CHAPTER-1-Introduction-to-Marketing.pptxCHAPTER-1-Introduction-to-Marketing.pptx
CHAPTER-1-Introduction-to-Marketing.pptx
girewiy968
 
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
ginni singh$A17
 
Universidad Camilo José Cela degree offer diploma Transcript
Universidad Camilo José Cela  degree offer diploma TranscriptUniversidad Camilo José Cela  degree offer diploma Transcript
Universidad Camilo José Cela degree offer diploma Transcript
taqyea
 
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
saadkhan1485265
 
Supervised Learning (Data Science).pptx
Supervised Learning  (Data Science).pptxSupervised Learning  (Data Science).pptx
Supervised Learning (Data Science).pptx
TARIKU ENDALE
 

Recently uploaded (20)

Potential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriatePotential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriate
 
the unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithmthe unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithm
 
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
 
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).docbai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
bai-tap-tieng-anh-lop-12-unit-4-the-mass-media (1).doc
 
ch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ssch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ss
 
NPS_Presentation_V3.pptx it is regarding National pension scheme
NPS_Presentation_V3.pptx it is regarding National pension schemeNPS_Presentation_V3.pptx it is regarding National pension scheme
NPS_Presentation_V3.pptx it is regarding National pension scheme
 
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
New Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service And N...
 
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
Celebrity Girls Call Delhi 🎈🔥9711199171 🔥💋🎈 Provide Best And Top Girl Service...
 
ISBP 821 - UCP 600 - ed).pdf banking standards
ISBP 821 - UCP 600 - ed).pdf banking standardsISBP 821 - UCP 600 - ed).pdf banking standards
ISBP 821 - UCP 600 - ed).pdf banking standards
 
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
 
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
VIP Girls Call Mumbai 9910780858 Provide Best And Top Girl Service And No1 in...
 
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy DsouzaOpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
OpenMetadata Spotlight - OpenMetadata @ Aspire by Vinol Joy Dsouza
 
transgenders community data in india by govt
transgenders community data in india by govttransgenders community data in india by govt
transgenders community data in india by govt
 
🚂🚘 Premium Girls Call Nashik 🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
🚂🚘 Premium Girls Call Nashik  🛵🚡000XX00000 💃 Choose Best And Top Girl Service...🚂🚘 Premium Girls Call Nashik  🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
🚂🚘 Premium Girls Call Nashik 🛵🚡000XX00000 💃 Choose Best And Top Girl Service...
 
Introduction to the Red Hat Portfolio.pdf
Introduction to the Red Hat Portfolio.pdfIntroduction to the Red Hat Portfolio.pdf
Introduction to the Red Hat Portfolio.pdf
 
CHAPTER-1-Introduction-to-Marketing.pptx
CHAPTER-1-Introduction-to-Marketing.pptxCHAPTER-1-Introduction-to-Marketing.pptx
CHAPTER-1-Introduction-to-Marketing.pptx
 
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
 
Universidad Camilo José Cela degree offer diploma Transcript
Universidad Camilo José Cela  degree offer diploma TranscriptUniversidad Camilo José Cela  degree offer diploma Transcript
Universidad Camilo José Cela degree offer diploma Transcript
 
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
High Girls Call Nagpur 000XX00000 Provide Best And Top Girl Service And No1 i...
 
Supervised Learning (Data Science).pptx
Supervised Learning  (Data Science).pptxSupervised Learning  (Data Science).pptx
Supervised Learning (Data Science).pptx
 

Data analysis and visualization with mongo db [mongodb world 2016]