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 |
|
| 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
Preservation of original source data
Lifecycle management and cold storage
Metadata capture
Managing governance, security, privacy
Self-service discovery, search, access
Managing data quality
Preparing for analytics
Orchestration and job scheduling
Reference Architecture on AWS
eCloudvalley’s Data Services
Data Lake & Data Warehouse design and implementation
Data Discovery & Data Modeling
Data Visualization through Tableau
Self-service Analytics portal
Machine Learning
eCloudvalley’s Data Solution
30+ deployments of data solution on AWS
AWS Data & Analytics Competency &
20+ AWS Certification on Big Data Specialty
Team of Data Architect and ML Engineer for your end to end data journey consultation
Success Stories
Consumer Goods Chain Stores for Report Automation & Interactive analysis
A leading Pan-Asian retailer involved in the processing and wholesaling of food and personal products […]
Global Retailers for Self-Service Analytics
A worldwide retail company which is highly diversified across 30+ brands, products, distribution channels and geographies with 50,000+ associates […]