Microsoft has introduced major changes to its traditional Enterprise Agreement (EA) licensing model, and these updates are forcing many organizations, especially mid-market companies with 500 to 5,000 users to rethink how they procure and manage Microsoft solutions. For years, the EA framework offered predictability, volume-based savings, and centralized management. Now, the … [Read more...] about The New Microsoft EA Model: What It Means and How to Win
Strategy
Learn everything about data strategy, what it should include in order to be successful, and how you can develop a data-driven business strategy for your business.
A Complete Guide to Blockchain Layers: From Infrastructure to Applications
When we talk about blockchain, we often hear terms like "Layer 1," "Layer 2," or "Layer 3." These labels aren't just buzzwords they represent different levels of a complex, layered architecture that makes blockchain networks work efficiently, securely and flexibly. Think of blockchain as a digital city, with a strong foundation, fast highways above, towering skyscrapers where … [Read more...] about A Complete Guide to Blockchain Layers: From Infrastructure to Applications
Ten Technology Trends That Will Shape 2026
The below is a summary of my new technology trends predictions for 2026. In a world accelerating faster than our institutions, our strategies and even our imagination can keep up, 2026 is arriving with the force of a bullet train. That makes this moment not just an opportunity to forecast, but a necessity to pause, reflect, and recalibrate. For 14 years, I've been mapping the … [Read more...] about Ten Technology Trends That Will Shape 2026
4 Reasons your Web Tracking isn’t Telling the Full Story – and What to do About it
When data is incomplete, every marketing decision is at risk. Without a full view of the customer journey, marketers risk misattribution, weak personalization, and misguided investments. To move from assumptions to accuracy, it's essential to uncover the weak points in your tracking setup. This article highlights four common blind spots - and how to fix them. 1. No … [Read more...] about 4 Reasons your Web Tracking isn’t Telling the Full Story – and What to do About it
How LLMs Are Changing the Way We Process Unstructured Data
Over 80% of business data is unstructured. Emails, PDFs, chats, medical notes, social media posts, videos-none of it fits neatly into rows and columns. Traditional tools struggle to analyze such data, leaving most of it unused.Large Language Models (LLMs) are changing that. By understanding natural language and context, they can turn unstructured information into usable … [Read more...] about How LLMs Are Changing the Way We Process Unstructured Data
+
What is data strategy?
Data strategy, also called analytics strategy or business data strategy, is the organizing principle for an enterprise’s investments in data and data-related technologies. Data strategy provides a framework for thinking through the complex trade-offs in managing data as an enterprise resource.
It helps business leaders make decisions about where to focus their data investments and how to maximize the value of those investments. Want to learn more about data strategy? Datafloq has courses available. Contact us to get started.
+
How does data strategy work?
Data strategy starts with a clear understanding of an organization’s business goals. From there, it defines the role that data will play in achieving those goals and outlines a plan for how to get the most value from data. Data strategy is an essential part of any organization’s overall data business strategy.
When done well, it can help organizations make better use of their data and gain a competitive edge. But when executed poorly, it can lead to wasted resources and missed opportunities. Data strategy is not a one-time exercise; it should be revisited regularly as an organization’s business goals and needs evolve.
+
What are the four big data strategies?
Big data can be a big help when it comes to making decisions for your business. But how do you make sense of all the data out there? One way is to use the four big data strategies:
- Performance management — Helps you track and improve your business’s performance.
- Data exploration — Helps you understand your data and find hidden patterns.
- Social analytics — Helps you analyze data to understand customer behavior.
- Decision science — Helps you use data to make better decisions.
These strategies can help you get the most out of your data and make better decisions for your business.
+
What should a data strategy include?
A data strategy should be designed to help an organization achieve its business goals. It should be aligned with the organization’s overall data business strategy to be effective, considering its unique needs, such as its size, industry, and geographic location.
The data strategy should also define the roles and responsibilities of those responsible for managing the data. Finally, the data strategy should identify the tools and technologies that will be used to collect, store, and analyze the data. By considering these factors, an organization can develop a data strategy to help it meet its business goals.
+
What is a big data strategy, and why should companies have the strategy in place?
Big data refers to a large number of data companies have access to. It can come from various sources, including social media, transaction records, and sensors. The challenge for companies is to make sense of this data and use it to improve their business.
A big data strategy helps companies to set goals and priorities for dealing with big data. It also helps them to invest in the right technologies and build the necessary expertise. Companies will struggle to get the most out of their data assets without a big data strategy. They will also be at a competitive disadvantage compared to those companies that have invested in big data.
