Data Driven Decisions

Data Driven Decisions

Identifying the data sources helpful to improve business is the first step if any data analytics implementation. Data aggregation includes.

  • Identifying internal & external data sources like databases, logs, twitter streams, sensor data.
  • Aggregating these data sets in big data cluster. Preprocess data incase it requires cleansing and formatting.
  • Create appropriate data store for easy access of data when required.
  • Combine static data sets, archives and streaming data under one unified big data store

Data Processing

Not all data sources publish data in ready to analyze form. Data processing makes the data ready by

  • Identifying all data formats and their compatibility with each other.
  • Combine multiple data sets without losing information e.g. combining multiple log files for running complex analytics job.
  • Dropping redundant information identified as junk.

Data Analytics

Analytics reveals insight hidden inside data. Data analytics covers

  • Creating algorithms and scripts to analyze huge data sets in parallel.
  • Create rules based on historical data analytics that can be used as-it-is or can be combined with latest data sets to generate recommendations.
  • Predictive data analysis to become informed about the possible future with occurrence probability.
  • Publish results in format suitable for various visualization techniques e.g. graphs, interactive map etc.

Data Decision Science

Data decision science explores recommendations generated from analytics and

  • Publish suggestive actions and the probability of their success.
  • Help business & operations team understand the analytics recommendations.
  • Map suggestions to actions with the operational team.

Application Integration

Any application can harness the true power of Hadoop, when the application tightly integrated with it. Alethe provides expert service to create custom APIs to connect the application directly to Enterprise Data Bag.