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Beginner's Guide to Data and Analytics

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Beginner's Guide to Data and Analytics

Analytics has become such a multi-faceted field that requires some basic knowledge. You don't need to spend years learning what data and analytics are, though.

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It's becoming quite common to find articles and think-pieces that tout the countless benefits and advantages big data analytics offer companies and organizations across all industries. What isn't as common is a clear idea of what data and analytics are. For most people, these two concepts were forgotten shortly after university and are used only tangentially. However, it's becoming quite clear that to be truly successful and find the best ways to constantly maintain an edge, understanding analytics is vital.

That still leaves the question of what exactly these concepts are. Data may seem like a simple concept but is nevertheless accompanied by several ideas that can make the difference between success and failure. Similarly, analytics has become such a multi-faceted field that requires some basic knowledge. You don't need to spend years learning what data and analytics are, though. Starting from the beginning can help paint a much clearer picture.

What Is Data?

In its simplest form, data is just information. Everything companies and consumers do online and even offline creates information. This information can be incredibly specific — including demographic data, behavioral information, and other personal details — or can relate to larger groups as an aggregate.

Major corporations like Facebook and Google can gather data from even the most seemingly innocuous activities online and use it to better optimize their services. This new massive stream of information has led to the creation of the field of big data, which focuses on datasets (groupings of information) that are simply too large to analyze with traditional systems.

Data by itself doesn't reveal much, and especially when viewed without context or method. To really understand what data is saying, there must be a method to clean it, organize it, and interpret it better — and this is where analytics comes into the picture.

What Is Analytics?

Analytics is the way we turn thousands of data points into meaningful insights that can be applied to business processes. Today, analytics has outgrown the academic sphere to play a central role in most companies' development and growth strategies. This is because analytics helps find patterns in data that can highlight areas for improvement, successful tactics, and even show potential trends for the future.

The field of analytics is an umbrella term for a variety of more specific areas, and it can be applied to almost any industry today with success thanks to advanced data analytics software. Moreover, modern technology like machine learning and AI have made analytics a much more accessible field and have expanded its uses outside of statistics.

So, How Do Analytics and Data Help Businesses?

Analytics needs data to work, and data that hasn't been sorted and analyzed is not very helpful. Data needs to be properly interpreted and organized to be useful, a process that includes removing data that isn't useful (scrubbing the data), organizing it into more logical groupings, and connecting data points to find patterns, insights, and useful information that might hint at future tendencies.

For most businesses, collecting data happens throughout several points in their production and value chains. Retailers, for example, collect data from suppliers, their own warehouses, points of sale, customer surveys, and even online visitors to their websites. All this information provides different insights and can be used for a variety of reasons including better marketing strategies, tailored promotions, value chain improvements, and operational fixes. Data analytics helps companies understand themselves better and lets them create better strategies based on their findings by turning data into actionable insights.

There are several key areas where implementing a regimen of analytics can be a major win for businesses. One of the first areas many companies look at with data analytics is inside their own operations. Companies consistently set goals, milestones, and objectives to reach, but tracking them isn't always easy. By focusing on the data teams and business segments produce, it's easy to create key performance indicators and have clear, tangible ways to measure them.

Similarly, analytics can significantly improve customer relations and support. Service, retention, and engagement are all based on the idea of understanding not just what customers want at a specific moment, but what they may want in the future. Using predictive analytics and visualizations, companies can see the areas where customers are satisfied, areas where they can improve, and more importantly, where these preferences may lead in the future. Marketing can also be greatly enhanced thanks to analytics. It's much easier to track success by measuring correlated data such as conversions, click-throughs, interactions on social media, and other similar measures before implementing findings in future campaigns.

It doesn't require a Ph.D. in statistics to dive into analytics. By finding the right tools and platforms to analyze and better interpret the data your company produces, you can start making smarter decisions to get a let up on your competition.

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Topics:
big data ,data analytics ,data visualization ,predictive analytics ,business intelligence

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