In recent years, there has been quite a buzz around the word data and its peculiarities impacting the overall business performance in a significant manner.
Data is of highest importance when it comes to building business growth strategies or simply taking an effective decision for the enterprise.
But the data that is available with the enterprises whether it is a large, medium, small or micro, it is in the raw form which is not of much use to the business.
Thus, the data needs to be analyzed precisely with the effective and dynamic data analytics process.
It is a trending topic among the enterprises in the market and is being readily adopted by the businesses for boosting the productivity of their workflow.
According to a business report,
- 94% of enterprises are considering data analytics as a crucial part of the workflow associated with growth and expansion of their business.
- 65% of the global enterprises are all set to increase their spending on data analytics as of this year 2020.
- 47% of the businesses have their data analytics platform on cloud that has escalated up from 39% in 2018.
In this article, you will be exploring every aspect of data analytics, right from its definition to the crucial steps you need to follow for getting your hands on the right data necessary for escalating your business growth.
Key takeaways from this article:
- What is data analytics?
- Why is data analytics so important for your business?
- What are the types of data analytics you need to know?
- Steps involved in data analytics process
- Future of data analytics
So, without any further adieu, let’s quickly start with the profound journey of data analytics.
What is data analytics?
Data analytics is the process of analyzing the collection of raw data and then discovering the crucial information as well as answers to certain questions from the data.
In simple words, it is the extraction of the valuable and profound information from the raw data that will help in increasing business workflow productivity and efficiency seamlessly.
Not to mention, it’s effectiveness in making precise and intelligent business decisions.
Why is data analytics so important for your business?
In today’s modern business world, traditional methods for accessing crucial data are of no use anymore. Businesses need to be faster and agile in their endeavour for meeting the customer requirements and to stay ahead against the competitors.
The main role of data analytics is to identify and uncover crucial information from the bunch of raw data of your enterprise as described in the above definition.
This crucial data empowers your enterprise to strategize and grab new opportunities for the business along with making precise as well as efficient decisions, promoting dynamic workflow, achieving higher customer satisfaction and thus better revenue system.
Here are the few of the many benefits associated to data analytics:
- Faster access to crucial business data
- Dynamic decision making
- Smooth business workflow
- Higher customer satisfaction
- Aggressive revenue cycle
Before we proceed further towards the steps of the data analytics process, let’s take a look at the types of data analytics for better understanding of the process.
What are the types of data analytics you need to know?
Data serves as the base for every business workflow associated with any domain and at every layer.
Thus it’s important that we know about the power of data analytics and it’s consecutive types to maintain the optimal performance.
Following are the 4 types of data analytics:
- Descriptive analytics
Descriptive analytics is the process of analyzing the past data associated with events or transformation in the enterprise to get a better and clear knowledge on the change occurring in the business.
Suppose your enterprise has just gone through a movement of data from one management system to another.
But unfortunately, the shift didn’t work out well and it was a failure.
Now, to find out what went wrong in the movement of data, descriptive analysis proves beneficial in uncovering the mystery.
Descriptive analytics helps you to get crucial insights of the past, from the raw data that are collected through multiple resources.
It’s not a completely reliable analytical process to go forward with as it will provide you with the data related to the part that went wrong during the data movement but not the why part of it.
This mostly helps in curating a strategic growth plan based on the analysis on the past data.
Thus, it’s advisable that you combine it with other types of data analytics for better analytical results.
- Diagnostic analytics
Unlike the descriptive analytics, the diagnostic analytics provides you the data associated with the “why part” of the event or transformation occurring in the business.
Considering the same example as above, we can determine why the failure occurred in the data movement procedure and resolve it effectively with ease.
Diagnostic analytics is an advanced form of analysis that runs an audit for the entire business workflow and determines the root cause as to why a particular outcome emerged.
With an in-depth knowledge of your particular enterprise problem, you can build sustainable and effective strategic business plans to resolve it effortlessly.
- Predictive analytics
Predictive analytics helps you look into future events, providing a brief detail on what is likely to happen.
This procedure uses both the descriptive and diagnostic analytics to dig in the latest trends, probable problems as well as exceptions, empowering your enterprise with valuable forecasting capabilities.
Although predictive analytics enables you to make predictions on the future events or any processes, it should be handled with care and minute attention.
The preciseness of the prediction from this process can even go wrong if the available raw data is of poor quality. Thus it’s necessary to ensure that the data quality is of the highest grade to achieve the best possible results as the outcome.
- Prescriptive analytics
As the name suggests, prescriptive analytics lists the actions that can be taken for eliminating a particular business problem of the present or that has the probability to occur in the future.
This process requires both the internal as well as external data to come to a strong conclusion. The efforts required in prescriptive analytics is more than the above 3 mentioned analytical types and also demands the use of machine learning, AI in combination.
Thus it’s important to consider the requirement of the business before choosing any particular analytics process for your organization.
Let’s take a look at the numbers for a better outlook into the use of the above analytical types among the enterprises.
According to the global survey of enterprise analytics, 2020,
- 59% of the enterprises rely on the descriptive and predictive analytics for more contextual insights on the business workflow and thus direct their decisions accordingly based on the right facts.
Every data analytics type is crucial on various layers of the enterprise workflow for driving effective and swift outcomes.
The use of a particular type depends on the various business factors such as size, industry type, competitiveness and much more.
Steps involved in data analytics process
For every enterprise, availability of data is not a problem but access to the right data for driving the required outcome is, that blocks the pathway towards making a clear and effective decision.
Thus, before you start with the data analytics process, you need to answer certain questions for smooth extraction of the right actionable data.
They are as follows:
Do you have the right set of data?
Does your data match the result you want to achieve?
Is the data powerful enough for stimulating your business decisions?
Answers to these questions will set a strong base for your data analytics and help you drive effective decisions for your business as you proceed further with the process.
Following are the 4 crucial steps of data analytics process you need to follow for your business:
- Create a set of questions in accordance to the result you wanna achieve
The first step towards getting the right answers for your business is to have the right set of questions.
It should be designed in such a manner that they possess the capability of detecting or eliminating the crucial information regarding the business goals you wanna achieve.
For example, take any particular business problem and examine it first to create a clearly defined question.
The nature of questions must be very clear and precise to the agenda of your enterprise.
- Build a strong and precise measurement parameters
The effective data analysis comprises strong and precise measurement parameters set for examining the growth.
This also requires the knowledge about what and how a particular part needs to be measured.
Setting strong measuring parameters not only helps to track the growth of the process but also saves a lot of your valuable time.
- Collect, filter and organize your data
Once you are prepared with the above two steps it’s time to collect, filter and organize your data for the purpose of extracting quality information from it.
Determine from which section you need to collect your data.
After that start with a file storming process and name alignment of the files as you move further with the procedure of collecting data. This helps your team members for not going through the same data again, saving time and energy.
Maintain your data in a systematic manner by filtering and organizing it at the central location for everyone’s access.
- Data analyzation
The final step is to analyze the data and extract the exclusive quality information to drive effective decisions through it.
Select the type of analytics mentioned above as per your business needs and execute it for generating the right information for your enterprise.
If you have got the answers for all your questions then you have successfully executed the process and you are ready to use it for the business.
Follow these 4 steps for analyzing the data and making better robust decisions backed by the right information.
The process of analyzing data will be a whole lot easier if it’s done with the help of a certain tool or software.
Future of data analytics
Data analytics plays a huge role in our day to day as well as our business lives. This astonishing technology is already impacting our lives optimally, enhancing the way we do things.
Especially if we look at it from the business aspect, most of the decisions are supported by it.
Companies are looking to increase the investment in data analytics practices for staying ahead in the competition and achieving better performance with every move.
According to a business survey,
The global market rate of this industry is $138.9 billion as of 2020 and is expected to grow further to $229.4 billion by 2025.
This is prevalent in both the mega as well as small and medium enterprises.
If we talk about the future of data analytics it is seen to achieve higher place not only in our business but also in our day to day lives changing the way we process things.
So, this was a complete overview of data analytics in a precise format.
We hope this proves to be of valuable knowledge for enhancing your business.