12 Tools and tech for modern data analytics
This chapter covers
- Key technologies for data-informed decision- making
- An overview of analytics and reporting tooling
- Self-service strategies used in data analysis
- Using artificial intelligence in your work
Data analytics is a constantly evolving field, driven by advancements in technology and a growing demand for data-informed decision-making. The methods we’ve covered throughout this book (e.g., hypothesis testing, parametric and non-parametric statistics), remain foundational to our work as analysts. However, the tools we use to implement these methods have changed significantly in just the last few years. This makes it necessary to evaluate whether you are delivering value efficiently and effectively.
Keeping up with the current landscape can be overwhelming. It seems like every week there’s a new vendor promising to eliminate pain points in your workflow. But what even are those pain points? How do you determine when to explore new tools to use, which tools will solve the problems you are experiencing, and how you can use these tools effectively?