Choosing the right analytics foundation often starts with understanding the difference between a data lake and a data warehouse. Both store data for analysis, but they solve different problems and shine in different moments of your data journey. The big idea: Flexibility vs. reliability. A data lake is a low-cost repository for all data types—tables, …
A data lake is a centralized repository that stores all types of enterprise data, including structured, semi-structured, and unstructured data, at any scale. Teams keep data in its raw form and apply structure only when reading it, which makes lakes ideal for fast ingestion and flexible analysis across many workloads. Key ways organizations use a …
If you’re exploring Microsoft’s Big Data stack, you’ll run into Azure Data Lake Analytics (ADLA) in older tutorials. Here’s the quick, search-friendly update: ADLA was Microsoft’s on-demand analytics service that let teams run U-SQL scripts at cloud scale and pay per job, without managing clusters. Microsoft retired ADLA on February 29, 2024; therefore, new implementations …
If you’re building a modern analytics stack, you’ll quickly run into two big terms: data lake and data warehouse. Both store data for analysis, but they were built for different purposes, and selecting the right one (or combining them) determines how quickly you can turn raw data into informed decisions. What is a data lake? …
NuSummit, a leading provider of advanced digital transformation and cybersecurity solutions for the global capital markets and financial services industry, today announced that it has achieved the Amazon Web Services (AWS) Service Delivery designation for AWS Lambda.
High-speed trades, real-time data, remote teams, and ever-evolving APIs define today’s capital markets environment. In such a scenario, old-school perimeter security doesn’t just fall short; it puts your entire operation at risk.
In financial services, the classic tech mantra “move fast and break things” just does not work. If you are in banking, insurance, or capital markets, you cannot afford to sacrifice trust, compliance, or system stability for speed.
Imagine this: Your AI-generated client report goes out—polished, professional, and completely wrong. The data is fabricated, a key metric is misinterpreted, and compliance red flags blink too late. The fallout? Reputational damage, regulatory scrutiny, and potential legal action.
In insurance, trust is everything. But as insurers double down on digital, they’re unintentionally pulling away from what customers value most—empathy, clarity, and human connection.
Business intelligence within data warehousing leverages information gathered in a data warehouse to deliver insights that support improved business decision-making. It transforms unprocessed data into valuable knowledge for an organization. NuSummit focuses on delivering Business Intelligence (BI) solutions through data warehousing, assisting organizations in converting raw data into usable insights. In essence, NuSummit utilizes data …
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