The pandemic has changed the way businesses work now and in the future. Post-crisis management has become the key focus for most industries. The impact has been unprecedented. The sweeping changes the virus has heralded globally are set to last far longer than this year. Business plans for 2021 have had to be shelved, with dramatic adaptations to working models being brought in … [Read more...] about Post-Crisis Management: How to Use Data to Pivot Growth Strategies
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.
Attribution Tool Selection Guidelines for Data-Driven App Development
Demand for mobile apps is exploding. By the end of this year, the market is estimated to be worth $189 billion. Advances in big data are shaping the market in interesting ways. It is important for developers to leverage data technology to their fullest advantage. Datafloq has previously discussed the importance of choosing the right tech stacks, but there are other platforms … [Read more...] about Attribution Tool Selection Guidelines for Data-Driven App Development
Win By Keeping Data Science Simple
Getting too fancy by using complex and layered data science approaches can magnify the issues in data instead of controlling them. This blog will explain why and illustrate with a real-world example that I also discussed in The Analytics Revolution to show that the old rule of keeping it simple fully applies to complex areas like data science. A Surprising, But Recurring, … [Read more...] about Win By Keeping Data Science Simple
Why Data Management remains a challenge in the Data and AI-first era
Data is the fuel of the modern organisation. As it's proliferated across the enterprise, more people are integrating it into their business and operational decisions. This means that having a robust data management strategy and infrastructure is critical for the success of every data-driven business. Nevertheless, data management remains a fundamental challenge to solve even … [Read more...] about Why Data Management remains a challenge in the Data and AI-first era
Improve Customer Service Experience: Take the AI Way
There is a lot more buzz around the need to improve customer experience than guidance on doing that. Major blame for the issues goes to the insatiable expectations of the customers. No matter how exceptional your customer service experience is, customers will get used to it within some time, and it won't feel exceptional. Hence, innovation is the fundamental driving force of … [Read more...] about Improve Customer Service Experience: Take the AI Way
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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.
