Data lake (warehouse)

Data mining from Big Data (4V's)
1. 4 V's
  1. Volume
    1. The simpliest
  2. Variety
    1. That is what really makes the data Big
  3. Velocity
    1. Delays significantly decrease the value of information
  4. Value
2. Finding patterns, clusters, corelations, predicting variable
ETL (Extract, transform and load)
1. Hadoop (open source). Bring algorithm to a data MapReduce
  1. To load or not to load Data to a Lake?
2. Streaming instead of batch update
Data governance
1. Or just liabilities?
  1. Data lake ->
    1. Lake may leak
    2. Data swamp ->
      1. Toxic swamp
Information assets
1. All kinds of information collected by an organization
  1. Structural
  2. Unstructural
  3. Semi structural information
Business objectives
1. Know your customer (KYC)
OLAP (olnine analysis processing)
OLTP (online transaction processing)
1. Collect and process the data at the moment of it's creation
  1. OLA (online action) due to user's activity, patterns, clusters, value prediction

Resource summary

	Created by Prohor Leykin almost 7 years ago