Any organization with a call centre or with customer-facing employees receive complaints and compliments on a daily basis. They talk to customers via the phone, email, messaging App or face-to-face and while doing that, they create massive amounts of data. Unfortunately, very few organizations actually use that data to improve their customer service. While in fact, that data … [Read more...] about How to Improve Your Customer Service with Big Data
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.
6 Issues to Consider when Monetizing Big Data
When discussing how companies can capitalize on Big Data, we often hear about successful use cases that have helped companies achieve various business goals, such as improving sales and efficiencies, strengthening customer relationships, and providing better products and services. Another way companies can capitalize on Big Data is by monetizing it. Data Monetization … [Read more...] about 6 Issues to Consider when Monetizing Big Data
A Big Data Cheat Sheet: What Executives Want to Know
In April, I was given the opportunity to present An Executives Cheat Sheet on Hadoop, the Enterprise Data Warehouse and the Data Lake at the SAS Global Forum Executive Conference in Dallas. During this standing-room only session, I addressed these five questions: What can Hadoop do that my data warehouse cant? Were not doing big data, so why do we need Hadoop? Is Hadoop … [Read more...] about A Big Data Cheat Sheet: What Executives Want to Know
How to Improve Customer Experience by Quantifying Multichannel Issues?
Every online professional knows that the usability of a website is a key factor in terms of the amount of sales it generates. Customer experience is the number one guideline when it comes to improving and optimising a website. If your data shows a drop in the amount of sales, there are several tools you can use to replay visits on your website. However, you should take some … [Read more...] about How to Improve Customer Experience by Quantifying Multichannel Issues?
360 Degrees Customer View and Its Web Data Collection Struggle
Every big company continuously tries to create relevancy by differentiating itself from the competition. Big data offers tremendous chances to do so, and therefore many companies choose to differentiate through data. They collect, process and distribute data for analytics and construct a clear view of the customer. This 360 degree customer view helps companies to define the … [Read more...] about 360 Degrees Customer View and Its Web Data Collection Struggle
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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.
