The Changing World of Business Intelligence
• Big Data: Hype or reality?
• Operational intelligence: does it require online data warehouses?
• Data warehouses in the cloud
• Self-service BI
• The business value of analytics
Overview of Analytical SQL Database Servers
• Are classic SQL database servers more suitable for data warehousing?
• Important performance improving features: column-oriented storage, in-database analytics
• Market overview of analytical SQL database servers, Actian Matrix and Vector, Dell/EMC/Greenplum, Exasol, HP/Vertica, IBM/Pure Data Systems for Analytics, Kognitio, Microsoft, SAP HANA and Sybase IQ, SnowflakeDB, Teradata Appliance and Teradata Aster Database
• The relationship between big data and analytics
• The Hadoop software stack explained, including HDFS, MapReduce, YARN, Hive, Storm, Sqoop, Flume, and HBase
• The balancing act: productivity versus scalability
• Making big data available to a larger audience with SQL-on-Hadoop engines, such as Apache Drill and Hive, CitusDB, Cloudera Impala, IBM BigSQL, JethroData, MemSQL, Pivotal HawQ, ScleraDB, SparkSQL, and Splice Machine
• Spark is in-memory analytical processing
• The interfaces: SQL, R, Scala, Python
• Does Spark need Hadoop?
• Use cases of Spark
• Classification of NoSQL database servers: key-value stores, document stores, column-family stores and graph data stores
• Market overview: CouchDB, Cassandra, Cloudera, MongoDB, and Neo4j
• Strong consistency or eventual consistency?
• Why an aggregate data model?
• How to analyze data stored in NoSQL databases
Data Virtualization for Agile BI Systems and Lean Integration
• Data virtualization offers on-demand data integration
• Seamlessly integrating big data and the data warehouse
• Market overview: AtScale, Cirro Data Hub, Cisco Information Server, Denodo Platform, Informatica Data Services, RedHat JBoss Data Virtualization, Rocket, and Stone Bond Enterprise Enabler
• Importing non-relational data, such as XML documents, web services, NoSQL and Hadoop data, and unstructured data
• Differences between data virtualization and data blending
New Business Intelligence Architectures
• Discussion of different BI architectures, including Kimball’s Data Warehouse Bus, Architecture, Inmon’s Corporate Information Factory, DW 2.0, the Federated Architecture, the Centralized Warehouse Architecture, the Data Virtualization Architecture, and the BI in the Cloud Architecture
• Do we still need data marts?
• What is the role of master data management in BI architectures?
• Using data vault to create more flexible data warehouses
• Data warehouse automation to create data warehouses and data marts faster
Operational Business Intelligence
• Analytics at the speed of business
• Different forms of operational BI: operational reporting, operational analytics, and embedded analytics
• What is time-series analysis?
• Integrating operational and historical data
• The role of data streaming engines, data replication, rule engines, complex event processing and ESBs
NewSQL Database Servers
• NewSQL stands for high-performance transactional SQL database servers
• Simpler transaction mechanisms to implement scale-out
• What does the term geo-compliancy mean?
• Market overview: Clustrix, GenieDB, MariaDB, NuoDB, Splice Machine, Pivotal GemFire XD, and VoltDB
New Forms of Reporting and Analytics
• Mobile BI, Exploratory analysis, self-service BI
• Collaborative analytics: the marriage of social networks and BI
• Tools for embedded analytics
• Investigative analytics and the data scientist
• R as the new open source platform for analytics
Data Modelling for Big Data, Hadoop and NoSQL
• Explanation of non-relational concepts, such as column families, hierarchies, sets, and lists
• Is storing unstructured and semi-structured data really more flexible?
• The differences between schema-on-read and schema-on-write
• Rules for transforming classic data models to NoSQL concepts
• Application needs influence database design