登录查看更多内容

What emerging BI trends should you discuss with your network?

由人工智能和领英社区提供技术支持

Business intelligence (BI) is constantly evolving and adapting to new challenges and opportunities. As a BI professional, you need to stay on top of the latest developments and trends that can impact your work and career. One of the best ways to do that is to discuss them with your network, whether it's online or offline, formal or informal. Here are some of the emerging BI trends that you should bring up in your conversations and learn from others.

此文章中的业界达人

由社区从 4 条内容中精选。了解更多

Dammy Adeniji

Data Engineer @ Access to Energy Institute | Azure Data Engineer associate | ETL Developer | Business Intelligence…
Suchandra Sengupta

Industry Solutions Architect - Cloud and AI | Generative AI
Alexey Anshakov

I ?? your business profits by up to 40% with automation. Unlock your first workflow automation case, saving you $25k+…

1 Data literacy

Data literacy is the ability to read, understand, analyze, and communicate with data. It's a crucial skill for any BI professional, but also for other roles and stakeholders across the organization. Data literacy can help you make better decisions, collaborate more effectively, and drive innovation. However, data literacy is not a given, and many people struggle with it. You should discuss with your network how to improve your own data literacy, as well as how to promote it within your team, department, or company. You can also share best practices, resources, and tools that can help you and others become more data literate.

添加您的观点

Dammy Adeniji

Data Engineer @ Access to Energy Institute | Azure Data Engineer associate | ETL Developer | Business Intelligence Engineer | Data Platform Engineer
举报内容
In large enterprises, it's often impractical for BI professionals to analyze every team's data in a highly tailored manner. A possible way to drive data literacy could be shifting from a central data warehousing model to a decentralized data mesh architecture complemented by regular training sessions. This way, team members have no choice but to get their hands dirty and extract useful insights from their domain data.

已翻译

赞
Alexey Anshakov

I ?? your business profits by up to 40% with automation. Unlock your first workflow automation case, saving you $25k+ in just 2 weeks, with a Forbes & EU Innovation Award recipient.
举报内容
My favorite advice is: use continuous learning strategy. Continuous learning is key in the ever-evolving field of data analysis. Staying updated with the latest tools and techniques is a must for professionals to remain competitive. Consider taking courses, attending workshops, or earning certifications to enhance your data literacy and stay at the forefront of your industry.

已翻译

赞

2 Augmented analytics

Augmented analytics is the use of artificial intelligence (AI) and machine learning (ML) to automate and enhance various aspects of BI, such as data preparation, analysis, visualization, and storytelling. Augmented analytics can help you save time, reduce errors, discover insights, and communicate findings more effectively. However, augmented analytics also poses some challenges, such as trust, transparency, ethics, and skills. You should discuss with your network how to leverage augmented analytics in your work, as well as how to address the potential issues and risks. You can also share your experiences, opinions, and questions about the benefits and limitations of augmented analytics.

添加您的观点

Suchandra Sengupta

Industry Solutions Architect - Cloud and AI | Generative AI
举报内容
Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms. It also augments the expert and citizen data scientists by automating many aspects of data science, machine learning, and AI model development, management and deployment. It has 3 main components- Machine Learning, NLP and Automation

已翻译

赞

3 Data culture

Data culture is the mindset and behavior that values and uses data as a strategic asset for the organization. It's not only about having the right technology and processes, but also about having the right people and culture. Data culture can help you foster collaboration, innovation, and performance across the organization. However, data culture is not easy to create and sustain, and many organizations face barriers and resistance. You should discuss with your network how to build and nurture a data culture in your organization, as well as how to overcome the common challenges and pitfalls. You can also share your stories, successes, and failures about creating and maintaining a data culture.

添加您的观点

Elijah Mutiso

Data analyst ||Data Modeler|| Data Architect || Data Engineer|| Financial Analyst || Statistics || Programming
举报内容
Augmented analytics combines machine learning and natural language processing to automate data preparation, visualization, and insights generation. It empowers business users to make data-driven decisions without deep technical expertise. I would like to point out how augmented analytics can democratize data analysis within our organization, making insights more accessible and actionable for non-technical stakeholders.

已翻译

赞

4 Data governance

Data governance is the set of policies, standards, roles, and responsibilities that define and manage the quality, security, privacy, and ethics of data. It's a vital component of any BI strategy, as it ensures that data is accurate, reliable, consistent, and compliant. Data governance can help you protect and optimize your data assets, as well as improve your credibility and reputation. However, data governance is not a one-size-fits-all solution, and it requires careful planning, execution, and monitoring. You should discuss with your network how to implement and improve your data governance framework, as well as how to balance the trade-offs between control and flexibility. You can also share your tips, challenges, and lessons learned about data governance.

添加您的观点

5 Data storytelling

Data storytelling is the art and science of communicating data insights in a compelling and engaging way. It's a key skill for any BI professional, as it helps you influence and persuade your audience, whether it's your boss, your client, or your colleague. Data storytelling can help you bridge the gap between data and action, as well as showcase your value and impact. However, data storytelling is not a simple task, and it requires a combination of technical, analytical, and creative skills. You should discuss with your network how to master and improve your data storytelling skills, as well as how to adapt to different scenarios and contexts. You can also share your examples, feedback, and recommendations about data storytelling.

添加您的观点

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Business Intelligence

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

What emerging BI trends should you discuss with your network?

1

2

3

4

5

6

1 Data literacy

2 Augmented analytics

3 Data culture

4 Data governance

5 Data storytelling

6 Here’s what else to consider

Business Intelligence

给文章评分

感谢您的反馈

更多Business Intelligence相关文章

更多相关阅读内容

What emerging BI trends should you discuss with your network?

1

2

3

4

5

6

1 Data literacy

2 Augmented analytics

3 Data culture

4 Data governance

5 Data storytelling

6 Here’s what else to consider

Business Intelligence

给文章评分

感谢您的反馈

查看其他技能