Welcome Data Crunch Listeners!

3 Tips for Effective Data Science Processes

  1. Don't over plan One of the most common data initiative failures revolves around too much central planning. Businesses move quickly, and the questions data scientists are trying to answer move even faster. Any process that’s counting on the world being the same tomorrow as it was today is going to fail. The best teams are often those that ship quickly, see what works, and iterate.
  2. There’s no one process that fits everyone. Analysts and data scientists come from all sorts of backgrounds. Some are former bankers and consultants who are most comfortable making presentations to execs in Powerpoint. Some are PhDs who’ve written popular R packages but have little industry experience. Others have been on frontend engineering teams before getting deep into data visualization. And others still are operations specialists who wrote managed enterprise Oracle databases for the last five years. While you should be comfortable asking your team to adjust to a process, you should also be willing to adapt your processes to better fit your team.
  3. “Waste” time. Data science projects can be like venture investing - the best projects can be 10-100x more impactful than the everyday wins. Even if they’re unlikely to succeed, data science leaders should make sure their teams have time to investigate these opportunities that have huge upsides. While it’s tempting - and often easier to justify to execs - to demand gradual progress every day, you’ll have a bigger longer term impact by uncovering just a handful of big wins.

Mode's Story

Mode believes data science and analytics teams should empower everyone in their organization to make better decisions. We deliver to thousands of teams daily with a streamlined end-to-end workflow, built the way data experts work.

How to Mode:
Connect your data warehouse.
Analyze with SQL, Python, or R.
Share across your organization.

Finally, a data platform you’ll want to live in

See how our Notebook and SQL Editor improve the speed and quality of iterative analysis

Mode adds value to any data stack

See how customers are using it

Your business isn’t drag-and-drop simple

Self-service dashboards are limited. Take reporting to the next level with D3, matplotlib, ggplot, and more.

Explore Mode’s completely customizable reports

"It used to take days for our analysts to go from a request for data to a report. With Mode it often takes minutes."

Denis Zgonjanin, Engineering Lead — Data Presentation, Discovery, and Governance

We don't want to eat your data stack

Mode plays nicely with others so you can deploy the best possible solution for each aspect of your infrastructure

Automate everything.
Equip everyone.

On demand

Refresh data anytime

Interactive

Help everyone explore data

Slack

Deliver data right where you need it

Permissions

Get the right data to the right people

Support

Live in-product chat

Learn from the Mode community with tutorials, example reports and visualizations.

Learn SQL

Pull, aggregate, filter, and join from databases.

Try it

Learn Python

Explore data visualization, modeling, and analysis.

Want to kick the tires for free?