Data Solutions 2019-07-31T11:01:38+00:00

Challenges to Enterprise Data Analysis

Decision makers know the importance of data analysis for accurate and faster decision-making processes. However, the traditional on-premises data warehouse and business intelligence tool may not support it. Nowadays, cloud technology is transforming the traditional way of analytics with agility, scalability, cost-effectiveness and machine learning capability by the concept of data lake and self-service analytics. Enterprise can hence cultivate the data-driven culture in the enterprise decision-making process in a timely manner.

  Traditional Analytic Journey Cloud Analytic Journey
Scalability with booming Data Growth Limited and rigid Highly scalable with on-demand consumption
Data Storage Typically on-premises Hardware Data Warehouse appliances, mainly for structured data only Data Lake for both structured and unstructured data
Cost Huge Capex investment
  • Pay-as-you-go pricing
  • AWS Redshift is 1/10 cost to traditional data warehouse cost
Approach Typically ETL Both ETL and ELT
Performance ETL time is 50% longer compared with Cloud Analytical approach due to limitation of computational power Significant reduction in ETL and ELT time by scaling of Cloud computational power when needed
AI/ML Capability Limited AI and ML capability at ease with prebuilt ML model and fast deployment

Attributes of a Modern Data Architecture

Automated and reliable data ingestion

Automated and reliable data ingestion

Preservation of original source data

Preservation of original source data

Lifecycle management and cold storage

Lifecycle management and cold storage

Metadata capture

Metadata capture

Managing governance, security, privacy

Managing governance, security, privacy

Self-service discovery, search, access

Self-service discovery, search, access

Managing data quality

Managing data quality

 

Preparing for analytics

Preparing for analytics

 

Orchestration and job scheduling

Orchestration and job scheduling

 

Reference Architecture on AWS

Reference Architecture on AWS

eCloudvalley’s Data Services

Setting up Data Lake and Data warehouse

Data Lake & Data Warehouse design and implementation

Data modeling and Discovery

Data Discovery & Data Modeling

Data visualization using Tableau

Data Visualization through Tableau

Self-service Analytics portal

Self-service Analytics portal

Adopting AWS prebuilt Machine Learning algorithm

Machine Learning

eCloudvalley’s Data Solution

deployments on AWS

30+ deployments of data solution on AWS

Data and Analytics Competency

AWS Data & Analytics Competency &
20+ AWS Certification on Big Data Specialty

Customer

Team of Data Architect and ML Engineer for your end to end data journey consultation

Success Stories

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