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What Is Insight And Analytics?

What Is Insight And Analytics?

posted in Product ● 19 Sep 2014

In a world where Big Data drives decisions and large enterprises are able to dramatically increase their effectiveness in sales, marketing and customer service through algorithm based decision making, the terms ‘insight’ and ‘analytics’ are thrown around a lot – but what are they?

Insight is defined as the capacity to gain an accurate and deep understanding of someone or something. Analytics, as the computational analysis of data or statistics.

Simply put, insight and analytics is the process of taking a source of data and gaining a better understanding of what this data means; the outcome of analytical behaviour can lead to insight. What does this mean for modern business?

Data is growing, businesses and organisations are overwhelmed with the amount of data that they can collect and receive from various sources. Without data analytics and data insight, this data is often useless, costly to store and can make data management difficult.


Understanding Data Discovery

Data reporting tools are one step to gaining data insight, but the real value of data discovery lies in the ability to tier data. Data discovery gives an understanding of what data exists, where it is stored, the age of data and can even help organisations understand when data was last accessed and how often. Different data from different sources will help give rise to different pieces of information and lead to different insights. For organisations who are business facing (B2B) the tangible benefits that can be gained from data discovery and data analytics will vary vastly from organisations who are end-user focused (B2C). Market leaders such as Google and Amazon are well-known for their ability to take data (enormous amounts of data at that) and turn it into an insight that will help them to make a new product or feature and continue as the market leader.

Discovery driven, Data Management

Undertaking the first step in data analytics and data insight will present a new challenge and opportunity around data management. Data analytics will generate new information and data, which must be securely managed and protected. However, it will also give an understanding of how best to store existing data. Data protection laws and best-practice advise that data should not be held for longer than necessary and primary storage systems are expensive. By understanding the age of data and how often is accessed, data can be tiered and if irregularly accessed can be archived away from primary systems for easier management. Data that is regularly accessed can remain on primary storage, ready for use.


A different data lifecycle

Managing and protecting data throughout its lifecycle is a challenge for many organisations, regardless of how much, or little, data is being held. The fact remains however, that data must be managed and protected, by turning data into information using data analytics, and then turning information into data insight, an organisation can start to see real return on the data it already holds.

Taking data through a process that eventually gives true data insight will be different in each use case. Although data analytics tools and data insight tools exist to assist in this process, what an organisation or business sees as value from data will change. The initial challenge around Insight and Analytics is gaining an understanding of what information will be of use. Aligning the use of data or understanding the insight required can be aligned with business goals to give more clarity on this. Many organisations will focus on:

  • Improving the customer experience
  • Increasing revenues by achieving more sales
  • Cutting costs by improving efficiency

Data insight and business goals

Using some of these high-level organisational benefits can show how data insight can have tangible benefits for an organisation. Improving customer experience is important for many, the knock-on effects can be longer customer lifespan, more spend or better reputation for an organisation. In an example where customers receive regular updates or newsletters from the vendor or supplier, the useful data will lie around interaction with that content. Collecting this data gives a baseline to analyse and may generate insight into the relevance or experience associated with that content – little or no interaction can be seen as a negative experience for the customer as they aren’t interested. To improve the experience, the vendor or supplier should then improve the content being sent and tie it back-in to a positive experience for the customer.


Actionable Data Insight

Data insight should not be the final stage of this process. Having insight can help make decisions or shine a clearer picture on a situation or process within an organisation, it’s how that insight is used that will deliver real value. Actionable insight, takes insight and turns it into an opportunity for an organisation to improve or change, giving a clear plan, direction or decision. By taking action on what has been gained from the data analytics process an organisation can achieve its goals, such as improving customer experience, as seen in the earlier example.






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