In recent years, the cloud has offered a scalable, versatile, and efficient environment for big data workloads. In this blogpost we explore how companies are deploying Cloudera Enterprise for running production Hadoop workloads - ETL, BI, advanced analytics, Spark - on Microsoft Azure, with enterprise-class data security and governance.
Hadoop Matters Blog
Big Industries' blog
Posted by
Matthias Vallaey on Feb 22, 2017 11:15:54 AM
What is a data lake?
A Data Lake is an enterprise-wide system for storing and analyzing disparate sources of data in their native formats. A Data Lake might combine sensor data, social media data, click-streams, location data, log files, and much more with traditional data from existing RDBMSes. The goal is to break the information silos in an enterprise by bringing all the data into a single place for analysis without the restrictions of schema, security, or authorization. Data Lakes are designed to store vast amounts of data, even petabytes, in local or cloud-based clusters consisting of commodity hardware.
Page 1 of 1
Subscribe to Email Updates
Contact Us!
Lists by Topic
- hadoop (9)
- Big Data (7)
- Big Data Architecture (5)
- Data Engineering (5)
- StreamSets (5)
- apache (5)
- big industries (5)
- cloudera (5)
- spark (5)
- Cloud Computing (4)
- Cloudera training tapas (4)
- Cronos (4)
- Data Lakes and Analytics on AWS (4)
- apache kafka (4)
- concepts (4)
- Confluent (3)
- Data Science (3)
- Hack The Future (3)
- Kafka Cluster (3)
- devops (3)
- hive (3)
- kafka (3)
- real-time streaming data (3)
- streaming (3)
- AWS (2)
- Altus (2)
- Amazon (2)
- Big Data Hackathon (2)
- Big Data on AWS (2)
- Cloud (2)
- Cloudera Altus (2)
- Cloudera Back up and Disaster Recovery (2)
- Cloudera Director (2)
- Cloudera Manager (2)
- Cloudera in the Cloud (2)
- Cloudera on Azure (2)
- Dare to Grow (2)
- Data (2)
- Data Driven Applications (2)
- Data Lake (2)
- Data Stream Processing (2)
- Distributed streaming platform (2)
- Feed the family Feel (2)
- GDPR (2)
- Hack the future 2017 (2)
- Hadoop Backend (2)
- Hadoop Projects (2)
- Hortonworks (2)
- MAPR (2)
- NoSQL (2)
- Python (2)
- SQL (2)
- SparkSQL (2)
- Streaming Data on AWS (2)
- Streamsets partnership (2)
- Your partner for Data Lakes and Analytics (2)
- analytics (2)
- big data processing (2)
- big data skills (2)
- cloudera navigator (2)
- cloudera navigator optimizer (2)
- cloudera user group belgium (2)
- cybersecurity (2)
- data integration (2)
- data science workbench (2)
- flume (2)
- impala (2)
- internships (2)
- meetup (2)
- mesos (2)
- share your wisdom (2)
- spark use cases (2)
- streaming data (2)
- #Techorama (1)
- API (1)
- AWS Cloud (1)
- AWS S3 (1)
- AWS VPC (1)
- Amr Awadallah (1)
- Apache Cassandra (1)
- Apache Hive (1)
- Apache Software Foundation (1)
- Apache Spark (1)
- Apache Zeppelin (1)
- Artificial Intelligence (1)
- Azure (1)
- Azure Marketplace Cloudera (1)
- BA4ALL (1)
- BDR (1)
- Big Data and GDPR (1)
- Big Data on Azure (1)
- Big Industries Academy (1)
- CDH (1)
- CQL (1)
- Cassandra Query Language (1)
- Cloud Event (1)
- Cloudera Data Science Workbench (1)
- Cloudera Fast Forward Labs (1)
- Cloudera IPO (1)
- Cloudera Sessions (1)
- Cloudera and GDPR (1)
- Cloudera market push (1)
- Cloudera on AWS (1)
- Cloudera on Azure Deployment Options (1)
- Cloudformation (1)
- Customer Insight (1)
- Customer Testimonial (1)
- Customer churn (1)
- Customer testimonials (1)
- DCOS (1)
- Data Intensive Applications (1)
- Data Modeling (1)
- Data Sources (1)
- Data wrangling (1)
- Datastax (1)
- Datastax Spark Cassandra Connector (1)
- Datawarehouse load and optimization (1)
- Developer (1)
- Document stores (1)
- EMR (1)
- ETL (1)
- Eben Hewitt (1)
- Enterprise Architecture (1)
- Enterprise Data Hub (1)
- HAProxy (1)
- HTF (1)
- Hackathon (1)
- Hadoop Adoption (1)
- Hadoop web applications (1)
- Hadoopable problems (1)
- IaaS (1)
- Information Security (1)
- Information Silos (1)
- Infrastructure as a service (1)
- Infrastructure as code (1)
- Jeff Carpenter (1)
- Job Opening (1)
- Kafka Meetup (1)
- Kinesis (1)
- Kudu (1)
- Lamot (1)
- Linux (1)
- MLlib (1)
- MNIST Data (1)
- Managing Servers in the Cloud (1)
- Mars (1)
- Martin Kleppmann (1)
- Messaging (1)
- MongoDb (1)
- Navigator and GDPR (1)
- New Hire (1)
- NewSQL (1)
- NoSQL Database (1)
- O'Reilly books (1)
- Online Search (1)
- Online ads (1)
- Operational excellence (1)
- PIG (1)
- PaaS (1)
- Platform as a service (1)
- Pydoop (1)
- Qlik (1)
- Qlik and Cloudera (1)
- R (1)
- Realtime (1)
- Risk (1)
- S3 (1)
- SAI (1)
- Scala (1)
- Search (1)
- Sensor data (1)
- Software Automation (1)
- Spark Streaming (1)
- Spark adoption (1)
- Spark market survey (1)
- Streamprocessing.be (1)
- StringIO (1)
- Tableau desktop (1)
- Telecom operator (1)
- Tensorflow (1)
- Tensorflow on Hadoop (1)
- Trifacta (1)
- Unix (1)
- Use Case (1)
- Utility outages (1)
- Vlaams Energie Bedrijf (1)
- algorithms (1)
- analogue.cloud (1)
- apache kudu (1)
- aws partnership (1)
- belgie (1)
- belgium (1)
- big industries DNA (1)
- business intelligence (1)
- cStringIO (1)
- career opportunity (1)
- cassandra (1)
- click fraud (1)
- cloudera user group meetup (1)
- cognitive (1)
- column oriented data stores (1)
- cronos group (1)
- customer retention (1)
- data collector (1)
- data correlation (1)
- data governance (1)
- data lineage (1)
- data models (1)
- data pipelines (1)
- datameer (1)
- distributed systems (1)
- docker (1)
- doug cutting (1)
- emre sevinç (1)
- energy production (1)
- exploratory data science (1)
- human brain (1)
- kubernetes (1)
- log files (1)
- machine learning (1)
- mapreduce (1)
- messaging systems (1)
- microsoft azure (1)
- online (1)
- online email provider (1)
- online retail (1)
- open source (1)
- pattern recognition (1)
- predictive analytics (1)
- project terra (1)
- realtime stream processing (1)
- robert gibbon (1)
- sensitive data (1)
- stage (1)
- stage opdracht (1)
- talks (1)
- targeting advertisement (1)
- training (1)
- twitter (1)
- user group (1)
- workshop (1)