Everyone’s talking about big data and data being valuable, but what drives the power within the data is something many of us are still unsure of. This blog will highlight the reasons why businesses must read the data carefully and how it brings value to their business; how data analysis is done; data analytics technology; and much more.
Data analysis leads to business intelligence. Strategic data-driven decisions always lead to efficient business operations and more business growth. Statistically speaking, the global data visualisation market revenue is expected to increase by 9.57 % over the next 5 years. By 2023, the global data visualisation market revenue is estimated at $7.76 billion.
Raw data has a lot of potentials, but you still need data analytics to unlock the power of data to use it and grow your business. Established and renowned data analytics firms work up on your data and make sure your data is correct before making sense out of it and culling insights.
Now let us delve further and understand how businesses can optimise their actions and utilise data.
What is data analytics?
In the simplest definition, the process of working with the data to draw insights and trends that are helpful for individuals and organisations is called “Data Analytics.”
With the aid of analytics applications, data analysts pull useful insights from the data.
An exploratory data analysis provides an overview and summary of the main characteristics of datasets. Businesses then use methods such as data visualisation to present the insights they’ve uncovered to wider audiences—including customers and clients—and suggest next steps based on those insights.
Let us understand different types of data analytics:–
So, there are four basic types of data analytics.
- Descriptive Analytics: In this kind, Changes or the activities that occurred during a certain period can be understood. For example, a decrease or increase in sales during a month or a quarter.
- Predictive Analytics: Based on the previous data, this analytics helps us to predict what is likely to occur in the time to come.
- Diagnostic Analytics: This analytics helps us identify the reason for a particular phenomenon to occur.
- Prescriptive analytics: This enables us to understand what course of action to take based on
To achieve correct predictions and insights for your business, the most important part is efficient data management, which includes data cleaning, data sorting, and data preparation. So, if your data is substandard, it may not give you the correct insights that can optimise your business decisions.
5 Key benefits of data analytics
- A customised customer experience: Data analytics provide more insights into your customers, allowing you to tailor customer service to their needs, provide more personalization and build stronger relationships with them.
- Informed business decision-making: Companies can use the insights they gain from data analytics to inform their decisions, leading to better outcomes.
- Simplify operations: Data analytics can help you streamline your processes, save money and boost your bottom line.
- Assess risks and deal with setbacks: Big data analytics can identify new risks from data patterns for effective risk management strategies.
- Enhanced business security:
How can businesses use data analytics to optimise their business?
Data analytics can help companies better understand their customers, evaluate their ad campaigns, personalise content, create content strategies, and develop products. Ultimately, businesses can use data analytics to boost business performance and improve their bottom line. It allows us to get valuable insights while saving effort. Most of the time, the data is stored in an unorganised format. Hence, it is tough to work on such data before data sorting and cleaning.
Here’s a step-by-step approach to how businesses use data analytics:
Before storing large volumes of data coming in from all sources, businesses have to be sure about their objective for storing data. Hence, planning and strategy are crucial before doing anything else concerning data analytics.
Collecting data: This determines which data sources they’ll be using, which data points they’ll be concentrating on, and how to collect that data. Some simply use transaction and social media data, while others use high-tech sources like GPS and RFID chips.
Ensuring data is relevant: Businesses have to ensure that the quantitative data they collect is relevant and that they know how to make sense of it.
Making effective use of data: Some businesses employ in-house data analysts, which can give them the edge over competitors, but for smaller firms, employing their own data specialists is unlikely to be viable.
Presenting data: The most vital part of data analytics is data visualisation – presenting findings and rendering them in a comprehensible format. There are commonly used Tools like Tableau, Salesforce, Tableau CRM, Microsoft BI and many more that help businesses visualise data in the form of charts and graphs.
It is always best to hire professional and expert data visualisation services, which would ensure your data is correct, will be able to do necessary research, calculations, and present your data in innovative and visually appealing dashboards.
Insights: it is one thing to gain all these insights via data analytics, but businesses must have an action plan to put them to practical use.
These insights provide insight into your audiences and campaigns, allowing you to improve you’re targeting and better predict future customer behavior.
Like any other profession, Data Analysis also has its own set of difficulties. Many times the data engineers and data analysis professionals also face certain challenges while working up on large amounts of data and pulling insights that are useful for your business.
Even for businesses, there are certain problems they generally face while collecting data for their business. Challenges generally faced by businesses related to data analytics –
- Data Collection
- Data Storage
- Data Accuracy
Technology for Data Analytics
Data analytics is nothing new. Today, though, the growing volume of data and the advanced analytics technologies available mean you can get much deeper data insights swiftly and easily. The insights that big data and modern technologies make possible are more accurate and more detailed. In addition to using data to inform future decisions, you can also use current data to make immediate decisions.
- Data Management
- Data Mining
- Machine Learning
- Predictive Analysis
Summing Up
The biggest businesses in the world are already practising data analytics and eagerly seizing on the opportunities provided by big data to help them know their customers inside out.
In retail, healthcare, hospitality, travel, eCommerce and many other sectors, data analytics is being used widely as it enables them in detailed understanding about their customers, sales patterns, and service and how to resolve potential problems.
The stark reality is this: If your business isn’t making good use of data science, then there’s a high chance that your rivals are. This puts you at a serious competitive disadvantage. Hence, if you take advantage of the opportunities of data analytics, your business is surely going to out win them all!