Index

A

  1. Advanced analytics
    1. banking
    2. cognitive
    3. government
    4. life cycle
    5. in-database
    6. in-memory
    7. model development
    8. model deployment
    9. predictive analytics
    10. prescriptive analytics
  2. Analysis
    1. analytical data set (ADS)
    2. e-commerce
    3. massively parallel processing
    4. processes
    5. sandbox
    6. scalability
    7. scoring
  3. Analytics
    1. traditional approach
  4. Analytical Data Set
  5. Analytic professionals
    1. data modelers
    2. data scientist
    3. scoring officer
    4. statisticians
  6. Analytics technology
    1. graphical user interface
    2. in-database
    3. in-memory
    4. model development
    5. model deployment
    6. open source
    7. predictive analytics
    8. prescriptive analytics
    9. visualization
  7. Automated prescriptive analytics

B

  1. Banking,
  2. Best practices
    1. hadoop
  3. Big data
    1. combine with traditional data
    2. variety
    3. velocity
    4. volume
  4. Big data sources
  5. Business analysts
  6. Business
    1. Use cases

C

  1. Centralized
  2. Churn
  3. Cleansed data,
  4. Clickstream data
  5. Cloud computing
  6. Collaborative data architecture
  7. Competitive advantage
  8. Customer behavior
  9. Cyber

D

  1. Data analysis
  2. Data exploration
  3. Data preparation
  4. Data quality
  5. Data scientist
  6. Data storage,
  7. Data warehouse
  8. Digital data

E

  1. E-commerce
  2. Economics
  3. Enterprise data warehouse
  4. Extract, transform and load (ETL) process

F

  1. Financial
  2. Foundation
  3. Future of data management
  4. Future of analytics

G

  1. Governance
  2. Government
  3. Graphical user interface

H

  1. Hackers
  2. Hadoop
  3. Hybrid cloud
  4. HDFS

I

  1. In-database
  2. In-memory
  3. In-database data quality
  4. Innovative
  5. Internet
  6. Internet of things (IoT)
  7. Investment
    1. in-database
    2. in-memory
    3. collaborative data architecture

M

  1. MapReduce,
  2. Massively parallel processing (MPP)
  3. Model development
  4. Model deployment

N

  1. Need for
    1. In-database
    2. In-memory

O

  1. Open source technology

P

  1. Performance
  2. Predictive analytics
  3. Prescriptive analytics
  4. Private clouds
  5. Public clouds
  6. Production environment

R

  1. Real-time
  2. Relational database
  3. Retail
  4. Risk

S

  1. Sandbox
  2. Scalability
  3. Security
  4. Semi-structured data
  5. Sensor data
  6. Services
    1. CaaS
    2. DBaaS
    3. DRaaS
    4. IaaS
    5. MaaS
    6. PaaS
    7. SaaS
    8. XaaS
  7. Social media
  8. Success stories

T

  1. Telecommunication
  2. Traditional data
  3. Transportation

U

  1. Use cases

V

  1. Variety
  2. Velocity
  3. Volume
  4. Vision
  5. Visualization

W

  1. Web data
  2. Web logs
  3. Workload
..................Content has been hidden....................

You can't read the all page of ebook, please click here login for view all page.
Reset
18.118.163.158