Heavily shattered by the pandemic, the retail sector is on the lookout for innovation. Among the many technologies retailers focus on, artificial intelligence is an undeniable leader. The market of artificial intelligence solutions for retail is projected to reach $23.32 billion by 2027, quite a leap compared to $5.06 billion in 2021. Within AI, computer vision and image … [Read more...] about Image Recognition in Retail: Applications & Implementation Tips
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.
7 ways AI revolutionizes cancer prediction, detection, and treatment
A human would say this was normal. But the AI was discovering these subtle patterns, and it was very confident. It was finding cancer. We just discovered this guy's lung cancer a year or two before we would have otherwise! This is what Mozziyar Etemadi, Biomedical Engineer at Northwestern University's Feinberg School of Medicine in Chicago, told Nature international journal. He … [Read more...] about 7 ways AI revolutionizes cancer prediction, detection, and treatment
Delivering The Right Level Of Analytical Detail
After a long, difficult analytical project is completed, how you deliver and position those results is as critical to success as all of the work done to get to the results. I've written in the past about not saying too much and taking your final presentation seriously. Here I will focus on a simple concept to follow to successfully get your business sponsors to act on your … [Read more...] about Delivering The Right Level Of Analytical Detail
Using Data Matching to Resolve Identity Resolution Challenges
Consumers interact with a brand through hundreds of touchpoints across devices, platforms, and channels. During the buyer's journey, consumers use 3-4 internet-connected devices. And by 2021, the number is expected to increase to 13 devices. This exponential increase in device usage indicates a sudden surge in data as well. This data influx is demanding organizations to have … [Read more...] about Using Data Matching to Resolve Identity Resolution Challenges
Top 7 Java Technology Trends Prevailing In 2021
Globally, Java is considered one of the most sought-after programming languages. If you want to select the latest Java technologies for your upcoming app development project, you must know these trends prevailing in 2021. Artificial Intelligence-Driven Applications Java is low maintenance, profitable and transparent technology. Its popularity has increased among AI app … [Read more...] about Top 7 Java Technology Trends Prevailing In 2021
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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.
