How modern data analytics drives decision making

Published on February 28, 2022

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Many people have referred to data as ‘the new oil’. While I agree with them, I believe it is also comparable to water. Like water supports human, animal and plant life, data is essential the life of modern businesses. 

The amount of data collected and created increases every day. You have data on your customers, operations, products, and competitors piling up everywhere. So, what are you doing to get the most from it?

How modern data analytics works

Modern businesses generate a significant amount of data on their internal operations and customer behaviour.

Data analytics is the process of examining these large data sets and transforming them into trends and patterns. You can then leverage this information when making business decisions or forecasts.

Data analytics allows you to make better decisions based on real-world evidence. It takes the data collected and makes it work for you by turning insights into actions.

Understanding data trends and reviewing potential solutions identifies opportunities and risks you might have been unaware of.

Most industries can derive insights from data analytics, including Customer 360 reports and real-time fraud detection with Artificial Intelligence (AI) and Machine Learning (ML).

Financial institutions might leverage it to predict default rates and manage risk. IT companies that manage massive server infrastructure can leverage it to highlight and resolve potential failures before they occur.

Why do you need modern data analytics?

With so much data at their disposal, businesses can now gain a competitive edge by harnessing the power of big data analytics. 

Data analytics enables you to target your customers more effectively with services and products by understanding their behaviour. You can improve customer experience via data on what customers expect when they reach out to you.

Then, you can ensure you have the resources to deliver to these expectations.

Analytics highlights areas where you can reduce costs and increase operational efficiency by identifying issues in your processes and forecasting potential problems.

Data analytics allows you to make better business decisions based on real-world evidence about your customers and internal processes.

By understanding the trends and patterns in your data, you can identify opportunities and risks that were otherwise invisible. You can then leverage this information to make changes that improve operational performance.

Four types of data analytics

There are four key types of analytics that you might leverage in your business:

Descriptive analytics summarise data trends and patterns into a format that is easy to understand. You might leverage it to find the answer about a particular outcome or analyse what is happening now.

For example, if a large number of people request a product demo every year in January, descriptive analytics would summarise this.

Diagnostic analytics identifies and diagnoses the reason something occurred. A high number of requests for a product demo in January might indicate that people prefer to deploy that product in their business early in the year.

Predictive analytics is a powerful tool for enhancing decisions by providing insights on potential future events. It relies on two main components: data and models.

The data trains the models, which then make predictions. For example, it will leverage historical data to predict when a product will be in high demand.

Prescriptive analytics is a field of data analytics that provides recommendations and guidance for decision making. It uses mathematical models to analyse data, identify patterns and relationships, and recommend actions based on those findings.

For example, if you know that your product will receive a high request for demos, you can ensure you have the resources ready to meet the demand.

Tools for enabling data analytics

Data lakes are repositories for storing unstructured or structured data. Their purpose is for an organisation to store all data collected in case they need this data in future.

Data warehouses provide the necessary infrastructure to store and analyse large amounts of data. Data warehouses help organisations make better decisions based on data-driven insights by enabling users to quickly access data.

The growing volume and variety of data have made data warehousing even more critical for organisations looking to leverage data analytics.

Thanks to the advent of big data technologies, data warehouses can now handle greater volumes of data more efficiently than ever before. As big data grows in importance, data warehouses will remain a critical part of any organisation’s analytics arsenal.

Data management tools clean and process data to help you get the most from it. They also make it easy to track and analyse changes over time to identify trends.

Data management tools automate data analysis, saving time and money because a person does not have to complete this process manually. Ultimately, using data management tools can help businesses better understand their data and how it affects their business.

Machine learning (ML) is when computers learn from data. ML algorithms require a lot of data to make predictions or decisions. The more data fed to the ML algorithm, the better it will become at predicting outcomes.

Getting the most from data analytics

As a business, it is important to ensure that you are using relevant data in your data analytics strategy. If you are unsure what data to use, there are a few steps you can take:

Identify your goals and objectives. Before you begin gleaning information from your data, you need a clear understanding of how you will leverage it for planning and strategy. For example, you might decide you want to understand how customers interact with your products and services.

Ensure the relevance of your data. Make sure you are only collecting data relevant to your goals and objectives.

Think about data analytics as more than reporting. Your data must answer your questions and be easy to understand for everyone across the business. It should accentuate successes, problems and potential solutions rather than be a page of graphs and numbers.

Take action and implement the insights you have gained from your data analysis to improve your business performance. Your data analytics initiatives will become meaningless if you do not action them.

Your actions might include mandating changes to business operations or altering a service to accommodate customer expectations.

How Experteq enables modern data analytics

Modern workplaces need robust data analytics to optimise internal processes and inform future plans for the business. Experteq understands modern data analytics, through and through.

We firmly believe in its merits, and we can bring these to your organisation.

Visit our Managed Services page for more information on our solutions.

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