eagle

Eagle was conceptualized to overcome major challenges of migration and focus on discovery, strategy and project plan. A unique tool that gives a deep analysis and provides a drill down capability to data warehouses and related ETL workloads. With a keen eye for precision, Eagle is able to detect inefficient and unidentifiable workloads, creating a detailed and interactive experience, breaking migration into a meticulous strategy.

features




Fast-paced 3 week assessment




Decipher complex data warehouse at a granular level




Complete understanding
Future state
Migration plan

OUTCOME



DETAILED MIGRATION
STRATEGY



A complete sprint-wise project plan powered by machine-based algorithms to break complex warehouse systems into logical chunks

PRECISE PROJECT
ESTIMATION



Logically analyzes a timeline, cost,
capacity and technology through
a deep study considering
all possible constraints

LINEAGE
WITHOUT GAPS



Captures end-to-end lineage to reveal
business logic and data flow across
varied technologies

OPTIMIZATION
RECOMMENDATION



In-depth study to identify optimization
opportunities and
recommended solutions

BENEFITS

analytics

  • Understanding the Data Warehouse ecosystem
  • Data layers
  • Stats gathering Data producers and consumers

transversal
analytics

  • Graph Identification and building
  • Establishing joins, depends on associations and accesses relationship

data
dependencies

  • Data flow pipes
  • Workflow and job flow hierarchies
  • Data Integration Modes
  • Join counts

data
classification

  • Hot/Cold/Warm data identification
  • Dormant data identification
  • Table statistics with details
  • Table statistics with details


data patterns

  • Data access patterns
  • Data update patterns
  • Data growth patterns
  • Data usage patterns
  • Data storage patterns

recommendation

  • De-normalization Recommendations
  • NoSQL Candidate Identification
  • Query Reusability
  • Indexes and Cache tuning

business logic

  • End to end data lineage
  • Column update logic
  • DML Counts
  • Type of compute

optimization

  • Data Model optimization
  • Optimize code and DDL
  • Batch window optimization
  • CDC Optimizations
  • Workload De-Duplication
  • ETL path Optimization
  • Duplicate data in multiple tables