Product Backlog grooming (also known as backlog refinement) is a recurring event or meeting where backlog items are reviewed and re-prioritized by product managers, product owners, and the rest of the team. The main objective of product backlog grooming is to keep the backlog up-to-date and ensure those backlog items are equipped for future sprints. Regular product backlog … [Read more...] about What is Product Backlog Grooming? What is the Goal of Backlog Grooming?
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.
3 Data Points That Help Ensure Supply Chain Visibility
The supply chain is the invisible backbone that powers modern industries. Every sector relies on a delicate chain of interconnected processes to deliver goods in optimal shape to customers. Electronification has made it easier to monitor supply chains and their logistics, but this doesn't mean it's an easy task. Research shows that data analysis and IoT devices are two of the … [Read more...] about 3 Data Points That Help Ensure Supply Chain Visibility
Taking Low-Code to the Next Level
A significant amount of both media attention and venture capital money has recently been given to low-code and no-code tools that focus on the areas of analytics, data science, and artificial intelligence. This blog will review the value propositions of low-code tools, discuss why the low-code trend really isn't new, and will then discuss how some companies are taking the … [Read more...] about Taking Low-Code to the Next Level
How To Leverage Data from OKRs Effectively To Drive Business Results
 As enterprises grow, they often find it challenging to keep their teams aligned with the proper responsibilities, duties, and powers. The only way to deal with this dilemma is to provide adequate support to all team members as they find their pacing. However, it isn't straightforward to drive effective business results in the meanwhile. Finding your OKRs, or Objectives and … [Read more...] about How To Leverage Data from OKRs Effectively To Drive Business Results
AI And Climate Change: How Technology Helps Reduce Emissions
According to Climate-KIC, even though we're still emitting 17% less CO2 than in 2019, our current greenhouse gas emissions still exceed the normal rate by 80%. And this is one of the most significant drops we've had in recent years. If this situation continues, the economic damage resulting from climate change will equate to sustaining one COVID-like pandemic every ten … [Read more...] about AI And Climate Change: How Technology Helps Reduce Emissions
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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.
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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.
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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.
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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.
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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.
