As marketers head to 2022, most of them need to ask themselves one critical question: Which search updates from 2021 should they be keeping in mind? Every year Google comes up with several algorithmic updates geared towards optimizing users' experiences and helping searchers discover the information they need as quickly as possible. One of the significant features of these … [Read more...] about Top 10 Google Algorithmic Updates of 2021 That You Must Know
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.
Making Governance Palatable
Governance of data and related analytical processes isn't something that most people get excited about. In fact, many people dread the idea of working under or even discussing formal governance policies. However, with some slight changes in thinking and positioning, the role of governance can come to be viewed more positively and as something that will be good for everyone. … [Read more...] about Making Governance Palatable
What Product Data Model Best Practices You Should Not Ignore?
Just like a roadmap or an architect's blueprint, a data model acts as a conceptual representation to facilitate more profound understandings of the storage and relationships of datasets in databases and/or data warehouses. This crucial task of linking data portfolios, characteristics, and interrelationships becomes even more mission-critical when the target database is … [Read more...] about What Product Data Model Best Practices You Should Not Ignore?
What is Product Backlog Grooming? What is the Goal of Backlog Grooming?
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?
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
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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.
