Apache Spark vs Databricks- the debate on the better choice for big data processing is always on. It’s a common question for teams working with large datasets, real-time analytics, or machine learning. Spark is the open-source engine that changed how we process data at scale. Meanwhile, Databricks, built by the creators of Spark, takes it further with a managed platform
Business intelligence spending reached new heights as organizations chase competitive advantages through data-driven insights and advanced analytics solutions. Yet many companies find themselves paying premium prices for enterprise analytics platforms that don’t integrate seamlessly with their existing Microsoft ecosystem and cloud infrastructure. Power BI now commands around 30% of the business intelligence market share while Tableau holds approximately 20%, but
Outdated reporting tools are holding businesses back. Many firms still rely on Crystal Reports, facing slow processing, rigid formats, and high maintenance costs. As data demands grow, businesses need faster, more flexible solutions to stay competitive. Companies that have migrated to Power BI are seeing measurable improvements. A Forrester Consulting study found that businesses using Power BI experienced a 366%
Transforming Employee Benefits’ Analytics Through Unified Business Intelligence
AI-Powered Answer Extraction for Enhanced Investor Servicing & Onboarding Efficiency
AI-Driven LPA Summarization for Fund Benchmarking & Regulatory Compliance
Elevating Data Maturity for a Global Packaging Leader
Enabling Real-time Compilance and Risk Detection Through an AI Agent
IT Infrastructure Optimization & Application Management with Power BI | Kanerika Case Study
Modernizing Pricing Systems for ABX with Kanerika's Automation Solutions
Delivering Contextual Query Resolution Through an AI Support Agent
Automating Accounts Payable with Kanerika’s Intelligent Solutions |RPA
