Did you notice most companies, irrespective of their size, are embracing Data Analytics these days?
From LinkedIn to Twitter, people are talking about analytics.
But why?
Why is there so much buzz for data analytics?
The reason is simple! Data is not just about numbers anymore.
It’s the new oil. However, it’s of no value if unrefined.
That’s where you need analytics.
Peter Sondergaard, Head of Gartner, said – If data is the oil of the 21st century, then analytics is the combustion engine.”
In 2021, 2.5 qunitllion of data were created per day.
And if you think it’s massive, wait for this year.
According to Finances Online, 94 zettabytes of data will be there by the end of 2022.
Data is now driving organizations and helping them make better decisions with conviction.
There has never been more data readily available for businesses to capture information from customers’ actions and use it to learn more about the target market.
So, if you aren’t utilizing the power of data analytics, you are not doing justice to your business.
What is Data Analytics?
Data Analytics is the practice of extracting significant insights from various data sets in the form of patterns, connections, and trends.
You can use data analytics to understand the trends and requirements of your customers.
It can help your business to improve company performance and product quality.
A simple example of data analytics could be the decisions you make in your life.
People make decisions in life based on their past encounters or how frequently they consider the potential effects of the choices in the future.
Similarly, when you utilize the data analysis approach in your organization, you will be able to
- examine the reasons for specific occurrences based on data
- comprehend your company’s aims & directions, and
- gain technical insights into the business
Types of Data Analytics
Descriptive: It tells what’s happening in your business. Like a fall in sales in a specific month/quarter/year.
Diagnostic: It analyzes why it’s happening. For example, if your sales have fallen to an all-time low or high. You can use this analysis to find out the root cause of the phenomenon.
Predictive: It predicts what’s likely to happen in the future. For example, the healthcare sector uses predictive analytics to determine the best course of action for each patient by predicting the outcomes of various treatments.
Prescriptive: It tells you what you need to do now. A prime example of prescriptive analytics is artificial intelligence (AI). AI systems continually ingest a lot of data to learn and utilize the knowledge to make wise decisions.
How Data Analytics Help Businesses?
Better Decision Making
The most apparent benefit of data analytics is the use of data to inform and justify crucial business choices.
You can anticipate what will happen in the future based on the data collected using predictive analytics.
While with prescriptive analytics, you can know how your organization should respond to these predicted changes.
For instance, a company can use a model to predict how changes in pricing or product offering would affect a client’s demand.
The company can make changes to offers to evaluate the validity of the hypothesis generated by such models.
Enterprises may use data analytics tools to assess the performance of the adjustments and visualize the outcomes after gathering sales data on the updated offerings.
Decision-makers can use it to decide whether to implement the changes throughout the company.
Streamline Business Operations
You can employ data analytics to improve operational efficiency, as most companies benefit from it.
For instance, gathering and analyzing data about the supply chains can help you pinpoint the bottlenecks in the process. It will also assist you in forecasting where future issues may arise.
Optimizing inventory levels is a challenge for many firms. It’s where data analytics can help.
Data analytics can assist in identifying the optimal supply for all the enterprise’s goods. It will check the characteristics such as seasonality, holidays, and historical patterns.
Personalized Experience
You can gain insights into customers’ behavior by employing data analytics to develop detailed customer profiles from this data.
Consider a grocery store chain with both a physical and online presence.
The business might combine data from its social media sites with information about its sales to assess both datasets.
Using those data, the company can run targeted social media campaigns to increase e-commerce sales for product categories in which customers are already interested.
Risk Management
A risk management strategy is a crucial investment, no matter the business field.
If the company wants to be successful, it must be able to identify possible risks and take steps to mitigate them before they emerge.
You can use data analytics to identify threats and implement preventative actions.
A statistical model that predicts future behaviors or occurrences can help you identify the area most vulnerable to theft.
You can use this information to decide whether or not to sell off any branch of your business.
Why Saisystems Technology for Data Analytics Services?
At Saisystems Technology, we will assess your data and develop it into a meaningful report to drive business choices.
- We assist businesses in building platforms that simplify incoming data and organize it into ad-hoc visual dashboards using data analytics and business intelligence (BI) tools.
- Our professionals are well-versed in deploying cutting-edge technology to manage enormous amounts of structured, semi-structured, and unstructured data from various sources.
- Our extensive knowledge in Data analytics ensures that you make the best decisions and reap the most profit.
- It will enable precise decision-making and assist you and your partners in possibly scaling and winning a competitive advantage in your market niche.
Want to know more about our services?
Explore data services use cases and case studies here.