Starting a small business is an exciting journey, but there are so many metrics to consider, especially when evaluating your success or demonstrating that success to stakeholders. Business finance is about so much more than the number of sales you make. Within the startup world, it’s common to hear of e-commerce companies implying that they are enjoying financial growth from the get-go.

In a previous article, we talked about the lost art of questioning and its importance when working with data and information to find actionable insights. In this article, we will expand on this topic and explain how questioning differs depending on what stage in the process you are from transforming data and information into insights.

At Mercado Libre, we are obsessed with unlocking the power and potential of data. One of our key cultural principles is to have a Beta Mindset. This means that we operate in a “state of beta”, constantly asking new questions of our data, experimenting with technologies and iterating our business operations in service of creating the best experiences for our customers.

Without a central place to manage models, those responsible for operationalizing ML models have no way of knowing the overall status of trained models and data. This lack of manageability can impact the review and release process of models into production, which often requires offline reviews with many stakeholders.

At the DataOps Unleashed 2022 virtual conference, AWS Principal Solutions Architect Angelo Carvalho presented How AWS & Unravel help customers modernize their Big Data workloads with Amazon EMR. The full session recording is available on demand, but here are some of the highlights.

Five things to know about customer profitability analysis: Digital retailers often talk a lot about 'profit' without ever determining the factors that drive profitability in their businesses. One of the biggest contributors to profit in e-commerce is existing and new customers who purchase products and services from online stores. However, the connection between customers and profitability can be unclear unless you carry out the right kind of analysis.

First, we collect data from an existing Kafka stream into an Iguazio time series table. Next, we visualize the stream with a Grafana dashboard; and finally, we access the data in a Jupyter notebook using Python code. We use a Nuclio serverless function to “listen” to a Kafka stream and then ingest its events into our time series table. Iguazio gets you started with a template for Kafka to time series.

As an ISV company selling a SaaS application, you have built analytics into your software because you know customers highly value insights into the data that's held within your application. Giving your customers business intelligence (BI) and analytics within your application offers them a window of insight into the data to help them optimize their business. You deliver more value which boosts end user adoption and means your client buys for longer.

We’re proud to share that the Iguazio MLOps Platform has been named a leader and outperformer in the GigaOm Radar for Data Science Platforms: Pure-Play Specialist and Startup Vendors report. The GigaOm Radar reports take a forward-looking view of the market and are geared towards IT leaders tasked with evaluating solutions with an eye to the future. GigaOm analysts emphasize the value of innovation and differentiation over incumbent market position.