You can't have a successful data migration if you don't map it out from the start. Learn what data mapping is and why it's an important early step in data migration and transformation projects.
Data mapping is an essential step in uncovering key insights from data. It helps establish relationships between different data entities while reducing data redundancies for more reliable data analysis.
Data mapping is also an important early step in several data movement and transformation projects. In this guide, learn about the different types of data mapping, how it works and some of the best data mapping tools on the market.
While Data Science practitioners, aspirants, and enthusiasts often get caught up in the business benefits of Data Science, it is equally important to keep a close watch on the common pitfalls that need to be avoided to launch a successful Data Science project.
By identifying and exploring why some initiatives fail, data scientists can learn to better leverage their data assets for maximum gain.
Let's begin with two Data Science roles: data scientist and data analyst. A data scientist must investigate a business problem by asking the right questions, gather the required data from different sources and prepare it for analysis, extract the actionable insights and communicate the results to others, and finally, deliver data-enabled solutions for positive business outcomes.
In this article, I will explain the four data-driven technologies, from a macro to micro level, that will drive change over the next 12 months and beyond. They will enable every business to make greater use of their data, improve business efficiency and serve their end customers better and faster than ever before.
Observability has grown up, breaking out from its infant stages as a tech-focused term to something that organizations realize will provide the key to keeping track of key data events in an increasingly de-coupled business world spanning systems architecture to the business operations it supports.
Moving forward, we now have the next level, 'Applied Observability', recognized by Gartner as a key 2023 strategic tech trend at its most recent Orlando Symposium.
The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe.
We're in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what's driving the success of our industry so we're in a unique position to publish our quarterly IMPACT 50 List. These companies have proven their relevance by the way they're impacting the enterprise through leading edge products and services. We're happy to publish this rapidly evolving list of the industry's most impactful companies!
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