Selling with Data #29 - Top 5 data innovations in 2023

I typically focus on the selling part of Selling with Data. In this article, I will focus on data.

Want to be the hit of the party? If that party is filled with data geeks like me, these 5 data innovations for 2023 will help.

1.????Synthetic Data

Synthetic data is hot right now. Imagine a data scientist needing data to train their models but the actual data contains private and sensitive information that consumers might not agree to use in the model development. Synthetic data is fake information that is made by a computer but resembles actual data well enough to train the models. It allows companies to test things without using real information from real people. According to a Gartner study, 60% of all data used in the development of AI will be synthetic rather than real by 2024.

Example: A hospital uses synthetic data to train a model to detect breast cancer in mammograms without having to use real patient data. This can help protect patient privacy and ensure that the model is not biased against certain groups of people.

Good question to ask: "How do you currently use or plan to use synthetic data in your business and what specific problems or challenges do you hope to solve with it?"

2.????Data Observability

Data observability is the ability to understand the health and the state of data in your system while it’s in motion and at rest. Essentially, data observability covers an umbrella of activities and technologies that, when combined, allow you to identify, troubleshoot, and resolve data issues in near real time.

Imagine that your critical data pipeline fails and causes downstream impacts to related pipelines, or a null record unexpectedly ends up in your data warehouse table and gets consumed.

Data observability will proactively send data incident alerts to your data team so they can resolve the incidents before it becomes a problem for data consumers.

Example: A company provides a complete dashboard of metrics on shipment logistics so customers can see all the pertinent information in a single place to make smarter decisions. As a result, it’s critical that this data is accessible and reliable. With data observability, they can track pipeline errors, schema changes, and other data quality issues at scale, that way, they can identify issues before they miss any SLAs – and resolve those issues faster.

Good question to ask: “How do you currently monitor and understand the performance and quality of your data, and what specific issues or challenges are you facing in this regard?”

3.????Data Privacy Regulations in 2023

In 2018, the first major data privacy regulation, General Data Protection Regulation (GDPR), was announced in Europe. Four years later, more than 100 countries had their own privacy or data protection laws, and that number will continue to grow in 2023. By the end of 2024, it is expected that 75% of the global population will have its personal information covered under privacy regulations. In the United States, California was the first state to create their own privacy policy, the California Privacy Rights Act (CPRA), that went fully into effect on January 1 2023. Virginia, Colorado, Connecticut, and Utah are following with their own policies this year. Each policy is typically slightly different and creates challenges for companies operating across multiple states or countries.

Good question to ask: "What are your current data privacy compliance requirements and how do you ensure that your company is meeting those requirements, including new requirements that are just being developed?"

4.????Data Applications

Data applications, or data apps, are business intelligence tools that do things. Data apps not only show data, but also execute downstream functions by the user interacting through the application. Companies use data apps to make their products or services better, like helping them sell more things, or to make their work more efficient.

Example: A major shoe retailer build a data app to not only track inventory of high demand sneakers, but also to allow store associates to order from the floor and ship directly to the customer, improving the customer experience and increasing sales.

Good question to ask: "How do you currently use data to inform business decisions and what specific areas of your business would you like to improve with the help of data applications?"

5.????Micro-SaaS

Micro-SaaS isn't specifically related to data, but I just heard the term a few weeks ago and thought it is worthy of the list for 2023. Micro-SaaS is a type of software that helps businesses with specific tasks. Full SaaS is a product with multiple services, such as Salesforce.com. Micro-SaaS only focuses on one or two services and does them well with available integration to other micro-SaaS services. My prediction for 2023 is that multiple startups will find success with only a small number of employees and micro-SaaS products that have very narrow and focused services.

Example: Using no-code or low-code applications, like Bubble.io, my son and I were able to create an MVP of a Micro-SaaS service that was able to help people write better messages using ChatGPT.

Good question to ask: "What specific tasks or processes in your business are currently challenging or time-consuming and how do you think a specialized software solution could help to improve them?"

Leave a comment with any other data innovations are you excited about in 2023, or comments on the 5 data innovations I listed.

A confession, ChatGPT helped me write some of this article.

Good Selling.