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Today, we are in the information age with a tremendous amount of data being created (as much as 90% of data being created in the last two years alone). This data comes from a wide range of sources and takes many different forms: human-generated documents and social media communications; transactional data that we use to run our businesses; and there is an ever-increasing proliferation of sensors producing streams of data.

Established in Florida in 1994, today, in 2018, the company has more than 1,135 outlets, in 44 US states, Puerto Rico and Canada.

Website visitors are 82% more likely to convert if they’ve chatted with the business beforehand. These marketers share how to start those conversion-worthy conversations.

In the development world, we’re constantly being bombarded by new innovations with the potential to change our world. 5G, augmented reality, machine learning… there’s probably never been a more fertile and exciting time to be a developer.

One big mistake I see organizations make when starting out on their data governance journey is forgetting the rationale behind data. So don’t just govern to govern. Whether you need to minimize risks or maximize your benefits, link your data governance projects to clear and measurable outcomes. As data governance is a non-departmental initiative, but rather a company-wide initiative, you will need to prove its value from the start to convince leaders to prioritize and allocate some resources.

As an entrepreneur and the CTO of a young startup, keeping a close eye on the product is at the top of my priorities. To keep improving the product, I’m always alert to new issues; and seeing those issues from different perspectives is key to resolving problems before users are affected. This is where monitoring comes in. In this blog post, I will get you into my stack and share the list of monitoring tools I’m using on a daily basis.