Sukesh Bera

Using streamlit to Visualize Data June 27, 2022 @6p ET

We’ll be exploring the Streamlit visualization tool and its features. We’ll check out data from DoorDash For Work and some other great sources in Streamlit to showcase its capabilities.

With so many different income streams, today’s restaurants have several different kinds of financial data to manage. Providing catering services, managing table reservations, or even running a food truck in addition to their dine-in business, makes it difficult to get a handle on all the different aspects of their operations.

Read more here.


Finance and accounting departments have lots of different data to manage—vendors, employees, customers, transactions, and investments, to name a few. This data often exists in different formats and silos, making it difficult and time-consuming to get a holistic view of the organization’s financial picture. And at the enterprise scale, this problem is magnified.

Read more here.

Think about some of the most common data visualizations you see in newspapers:

  • Graphs showing a country’s GDP growth
  • Stock market trends
  • Charts that capture business performance year-to-date
  • Rates of inflation

While most of these mean different things, they’re all the same at their core—they are all based on time series data.

Read more here. 

line graph

In today’s consumer market, retail stores benefit from making data-driven decisions. Gone are the days of relying on intuition for marketing, understanding consumer behavior, determining inventory decisions, and more. Instead, we’ve seen a rise in an area known as retail analytics. The goal of this post is to provide an overview of retail analytics, common use cases, and how this can be used to improve a company’s ROI. Read more here.

It’s common to find applications of machine learning in a variety of business areas, such as marketing, operations, automation, security, financial management, and more. The goal of this article is to review 12 companies that are using machine learning to make a difference in their industry.

Which industries use machine learning the most?

Organizations are turning to the cloud to handle increased data volume, velocity, and variety. Cloud data warehouses (CDWs) like Snowflake provide the flexibility and scalability necessary to support a modern data strategy.

And to bring all of their disparate information to a single source of truth, organizations rely primarily on two approaches: extract, transform, load (ETL) and extract, load, transform (ELT).

But before we dive into ETL vs. ELT in Snowflake, let’s clearly define each process.

the elt process

In this article, we will introduce the concept of people analytics and how HR and data professionals can leverage their knowledge and skills to make data-driven decisions.

The following list presents three easy ways to get e started with HR analytics: Read the article here

data cloud

In this article, we’ll give you a quick overview of categorical data, how to visualize it using the most popular methods, and the best tools your business can use to visualize this data. Read the full article here.