Maven for Data Leaders

Don't just gather data; understand it. Your organization has the data. But does your team have the skills? Here's where we think you should focus: Get into a data mindset by... - focusing on the business problem - improving data literacy skills - building a data culture Improve technical skills like... - collecting data - analyzing data - visualizing data What do you think? Are we missing any “must-have” data skills?

The difference between using Excel and using Excel WELL translates into hours (if not days!). Excel is used in almost every business in the world. (But that doesn't mean it's used efficiently...) How does your team measure up? - Do they know basic functions? - Can they transform data with pivot tables? - Do they have advanced skills in Power Query and Power Pivot? - Can they leverage Copilot in Excel to solve real-world data analytics problems? Learning to use Excel well can save hours of time and frustration.

5 reasons why your team could benefit from upskilling in Excel: - The organization wants to embrace technology - Your new hires have varying levels of proficiency - Team members have gaps in their Excel knowledge - You want to automate repetitive tasks and save time - Everyone THINKS they're an Excel expert... but they're not 😉 Excel is one of the most versatile and widely used tools in the business world, no matter what industry. Can your team use it efficiently and effectively? P.S. your team can sign up here for a FREE Maven account and take our Excel practice assessment 👉 https://lnkd.in/eRerrSQj

Don't trust your gut. (at least when it comes to making business decisions!) Our recommendation? Rely on data instead. How? Here's 6 steps to effective data-driven decision making: 1️⃣ Identify the problem ↳ Are you aligned on requirements, project scope, and outcomes? 2️⃣ Define success ↳ Is everyone using the same benchmarks and metrics for success? 3️⃣ Collect and prepare the data ↳ Is your data reliable, trustworthy, and of high quality? 4️⃣ Analyze and profile the data ↳ Have you found actionable insights that influence business decisions? 5️⃣ Communicate findings ↳ Do your stakeholders understand the importance of your findings? 6️⃣ Advocate for action ↳ Talk about what should happen next…based on the data! Use data over gut instinct or intuition to drive business decisions.

Our world RUNS on data. Does your team know how to use it? (and we're not just talking to the data teams here!) Whether you're a marketer using data for customer segmentation, an HR manager using data to analyze employee performance, or a finance professional using data for forecasting, EVERYONE needs to have a basic understanding of data. That's why we put together our Data Literacy Foundations Learning Path, where we... - introduce foundational skills working with data - provide frameworks for strategic thinking & measurement planning - apply skills with real-world projects & business cases This path is for everyone, from data professionals to organizational leaders and beyond! What do you think? Have you taken a look at our Data Literacy Foundations Learning Path yet?

Power BI is one of the best and fastest-growing business intelligence tools on the PLANET. Can your team use it effectively? Aaron Parry came up with a solid roadmap that can take your team from beginner to expert in Power BI! Here's what he suggests... - Get to know Power BI Desktop ↳ Get familiar with the interface and understand Power BI's workflow - Connect and shape data ↳ Learn how to connect to source files, shape and transform tables, and use query editing tools - Create a data model ↳ Learn table relationships so that you can blend your data into a single data model - Add calculated fields with DAX ↳ Build brand-new calculated columns and measures for your data model with Power BI's formula language - Visualize data with reports ↳ Get familiar with the "Report" view and the location of the tools and options available - AI visuals ↳ Explore Power BI's AI-driven visual tools but exercise caution From there, the sky's the limit! What do you think? Anything you'd include in this Power BI roadmap?

How data team leaders can help their team add value: - Foster a culture of continuous learning. - Align team goals with business objectives for impact. - Provide access to advanced analytics tools and training. - Encourage cross-functional collaboration for holistic insights. Data teams thrive when supported with resources and a collaborative environment. Empower your team to drive meaningful, data-driven strategies.

One of the worst traps a data team can fall into: Starting a data project without a solid measurement plan. Companies need data teams who can break down any project and build a measurement plan that will help the organization... - identify goals - understand outcomes - optimize performance to drive the business to new heights Here's where we think you should start: 1. Think business first 2. Know your audience 3. Define the KPIs and metrics 4. Identify the data sources you'll need We have a guide that goes deeper AND gives you a great place to start 👉 https://lnkd.in/emBBiExB

Is your team using AI? It's already having a HUGE impact on the data industry so if they're not, they likely will be in the future! What does that mean for you, as a data leader? Have you thought about how to handle AI and the rapidly changing environment of the data industry? No matter if you've just started thinking about it or if it's been on your mind for a while, this one's for you. Director of Analytics & Data Science Joe Squire joined us last month to talk about leadership in the age of AI. He talked about... - the best practices for building and leading strong analytics teams - the ways AI is changing analytics and where the industry is heading - how leaders need to be thinking about AI and the long-term impact on their teams ...and much more! Check out what else Joe had to say here 🎧 https://lnkd.in/eev78A-n #data #analytics #ai #artificialintelligence #businessintelligence

Leading a data team? Understanding the types of analytics is crucial for your team's success. Descriptive analytics ↳ Answer: what happened? ↳ Looks at historical data. Diagnostic analytics ↳ Answers: why did it happen? ↳ Analyzes at the root cause. Predictive analytics ↳ Answers: what will happen? ↳ Forecasts future trends. Prescriptive analytics ↳ Answers: what should we do? ↳ Recommends actions. Does your team knows when and how to use each type of analytics?