Our Consulting Strategy
In general, big consulting firms are responsible for big transformational programs. Having said that, time and cost associated with these programs are huge. This may not suit for small to mid size digitization initiative. INVINCIX plays a vital role by bringing a unique outcome driven consulting program that will suit for small to medium size programs.
This outcome driven consulting program is tightly coupled to our “Digitization of Application” program. This program drives the implementation of its’ strategic goals in a quicker and easier way to improve its’ operations and business outcome.
“First Thing First” Health Check
Database Unavailability
Impact on Performance
Data Growth & Capacity Planning
High Availability & Disaster Recovery
Increase in Productivity
Preparedness for Business Growth
Process
Database Overview
Initial overview of the database to validate the structure and schema.
Data Profiling
Detailed analysis of the rows and columns containing the data. Understanding data structure content and relationships.
Infrastructure Monitor
Administrative analysis of the database server made for each client with continuous & real time of resource utilization.
Scope of Tuning
Encompassing the activities aimed at optimizing the database performance.
Strategy
Key Areas of Database Performance Monitoring
CPU Usage
Monitor CPU usage to ensure that the database server has enough processing power to handle queries and other operations.
Memory Usage
Track memory usage to ensure the database has sufficient RAM for caching and processing.
Disk I/O
Monitor read and write operations on the disk to identify bottlenecks in data retrieval and storage.
Compliance
Ensure adherence to legal and regulatory requirements (e.g., GDPR, HIPAA, PCI DSS).
Encryption
Monitor the use and effectiveness of data encryption both at rest and in transit.
User Activity
Track user activities to detect unusual or unauthorized behavior.
Data Loss Prevention (DLP)
Prevent unauthorized data transfers and leaks.
Vulnerability Management
Identify and mitigate vulnerabilities in the database and associated systems.
Incident Response
Prepare for and respond to security incidents effectively.
Our Approach
01
Assessment
- Initial assessment
- Data profiling
- Database overview
02
Planning
- SLA
- Resource allocation
03
Execution
- Process
- Strategy
04
Monitoring
- Performance monitoring
- Continuous health check
05
Reports & Documentation
- Templatization
- Analysis & reporting
- Final documentation
Proposed Team
Tools We Suggest
Additional Suggestion
Data Security
We’ll consider both access to the server (at the network level) and the security of the data itself. We’ll report on what additional security options are available to you to further improve the security of your data.
Capacity Planning
Capacity planning is concerned with how well your SQL Server environment will cope with these changes in the future. Our database health check will seek to understand your workload and tell you how hard your database server is working today, so you can be pro-active, not re-active, and take action now before it causes problems for your users and applications.
Disaster Recovery
DR isn’t just about having backups, it’s about being ready to implement a backup and recovery strategy that works for your business. We will review your current DR strategy, establish your current Recovery Point Objective (RPO) and Recovery Time Objective (RTO), and then show you how to get to your desired RPO and RTO.
Case Study 1
Problem Statement:
Batch job was taking 4-5 hours
Our Approach:
- Identified major table involved in the batch job.
- Instead of just gathering stats, we followed defragmentation approach.
- Addition to that we performed some query tuning as well.
Improvement:
Earlier - 5hr
Now - We were able to 2.5 hr for the batch job
Case Study 2
Problem Statement:
Processing of VLT (Very Large Tables)
- While processing for any VLT, for each and every query, it scans the entire block even though it is not required.
- To process one table, usually it takes more time as it very large around 1GB.
- The tables are not in parallel processing.
Solution:
- Suggested to create partition along with sub-partition on the table, so when we write a SELECT query, for example within a timeframe or date range and enterprise specific only.
- Suggested to create a couple of valid partition index.
- Exchange partition.
- This saves a lot of I/O time.
Improvement:
- Pipeline process is much faster
- Better table management
- Compressing old partition tables
Earlier - 5hr
Now - We were able to 2 hr for the batch job
