Data is the currency of the modern economy. For businesses to succeed, they must be able to collect, analyze and act on data to make decisions and find opportunities. But there is a problem. Data is often incomplete, inconsistent, and often represents only a small slice of the whole picture.
Data Science is a fast-growing field – and with good reason. The right data scientists can make a huge impact on an organization, solving complex problems, finding hidden insights and helping their companies to make better decisions in a data-driven world. So it’s no surprise that Data Science is one of the biggest feel-good job markets out there today. But what if you’re not in that position?
there-you’re we’ve all been there-you’re working on a project together, and you and your teammate have two completely different versions of the same thing. It’s frustrating and confusing, and it makes you want to pull your hair out. It’s a common problem, and it happens for a lot of reasons—but one of the most common is that you’re looking at the same data but coming to different conclusions. That’s where Consensus In Data comes in.
Data is the backbone of our digital economy. It helps us make better decisions, build better products, and improve our lives. But when it comes to data, we don’t always have a say in what we see. We’re often at the mercy of a handful of tech giants who control what data is available, how we access it, and what we can do with it.
When data is used to make decisions, the results can be life-changing. Deciding to undergo a medical procedure, invest in a new business, or take a job offer are all decisions that rely, at least in part, on data. At its best, data is used to make decisions that are good for the individual or group making them and the people they affect. But making good decisions is hard. We have to weigh the needs of the person making the decision, the people who will be impacted by the decision, and the needs of the people who are making the decision. Our decisions are often made on incomplete information, and we don’t always have the full picture. When we’re making decisions together, the complexity grows exponentially. But when we’re working together on the same data, we can make better decisions together.
decides We don’t always have the same data, or someone else makes them together.
Sometimes, we’re at odds over what the data is telling us—or even if we’re looking at the same data. When that happens, we have to figure out how to come together—even if we don’t all see the same thing. That’s where Consensus In Data comes in. We’re a platform that uses AI and human moderators to help people find common ground.
Transformation! 