Data Analysis seems to be everywhere you look in the software development business.
It is a valuable tool for every development process step, with benefits going over even after delivery.
That's why we'll look into two related topics: Big Data and Data-Driven approaches in Software Development.
We'll give you an overview of both concepts, delving into their benefits and relevance.
Then, we'll look at Big Data applications, how Big Data and AI relate, and how to develop a data-driven mindset.
Finally, we'll examine the significance of Big Data and Data-Driven approaches.
What is Big Data?
The term "Big Data" is pretty straightforward.
It refers to extracting meaningful insights by analyzing massive, complex data collections.
This amount of data usually exceeds the traditional database software's analysis.
Let's take a look at its main characteristics!
The 5 Vs of Big Data
- Volume. The size of data can be measured is in terabytes, petabytes and exabytes. While in 1999, one gigabyte got the name Big Data, today, it start at terabytes.
- Value. The value of Big Data stems from insight discovery and pattern recognition based on specific processing protocols.
- Variety. Big Data includes different types of data, like unstructured, semi-structured, raw, and dense data.
- Velocity. Velocity applies to the speed at which information gets accumulated. Data won't be as valuable if you can't process considerable amounts fast enough.
- Veracity. This quality relates to how reliable or accurate the data is, which can be the most challenging part to control.
How is Big Data Collected
Data is everyone, but sometimes it is challenging to realize its scope.
For example, we generate about 1.7MB of new data per second!
Also, there are over 50 billion smart devices around the world that can create and analyze data.
If that sounds too vague, below are some of the primary sources of Big Data.
- Social Media. With a large percentage of the world’s population using social media, every photo or video, comment and message creates data.
- City Sensors. Many cities collect data on weather factors like temperature and humidity. Traffic and security cameras may collect other data types.
- IoT Appliances: Appliances connected to the internet are increasing, and Internet of Things also collects and stores data.
- Customer Feedback. Companies may ask you directly about aspects of your experience such as quality, timelines and satisfaction.
- Transaction Records. Financial transaction records, whether it’s an eCommerce transaction, banking, or a business one, have data behind it.
How is Big Data Used?
Now that we know where big data comes from, let’s see its use.
From what we’ve seen so far, one might understand that big data is only a way for businesses to make money.
Yet, this information gets used for a wide variety of applications.
These can result in long-term benefits for everyone.
Let’s look at some of them!
- Healthcare. Hospitals can use patient data for evidence-based medicine to save time and reach diagnosis in less time.
- Entertainment. Entertainment companies use data to offer tailored recommendations to specific audiences.
- Traffic Control. Big Data gets fantastic usage to manage traffic in cities where congestion is a big issue.
- Manufacturing: Here, Big Data reduces product defects, improves quality, and increases efficiency.
- Search Quality: When using Google or other Search Engines, data gets used to improve results and improve over time.
Big Data and Artificial Intelligence
Many people have questions about the relationship between Big Data and AI.
In this context, AI uses data to improve, and the more considerable the amount of data, the better.
So, Big Data plays a crucial role in Artificial Intelligence's results accuracy.
Yet, the relationship between Big Data and AI goes the other way.
This means that Artificial Intelligence is necessary to process these amounts of data.
As a result, Big Data and AI have a symbiotic relationship.
Moreover, it's expected this bond will lead to AI feeding Big Data to itself.
At the same time, it will make data analytics less labor-intensive.
Not too far from now, we'll see Big Data and AI combinations making our lives easier.
Big Data And Data-Driven Software Development
When it comes to Big Data, like with AI, there is a two-way relationship with Software Development.
Developers are creating apps that use big data. Meanwhile, they're using Big Data to streamline development processes.
If you use Big Data in a dev process, it inherently means using Data-Driven Analytics.
As Data-Driven becomes the standard in Software Development, this is only natural.
Moreover, you get the benefits of both a Data-Driven approach and Big Data.
You can increase your revenue and efficiency and decrease decision bias.
A highlight is that Big Data Development is not for everybody.
It takes fast processors and sophisticated software analytics.
Yet, if you could leverage a Data-Driven process, you'd also get near real-time analysis.
And as you may know, this is an invaluable tool in Software Development and Testing.
Another relevant thing is that, as we've mentioned, it's not all about business and profits.
Over the last few years, many studies have seen the light.
Within these, a constant is the unique possibilities of complete integrations.
What is a Data-Driven Approach?
Data-Driven approaches are those when decision processes rely on data analysis and interpretation.
When making decisions, you rank data over experience or intuition. Further, data must be accurate and relevant for a data-driven approach to succeed.
Why is Data-Driven Decision-Making Important?
Data-Driven decisions reduce risks, save costs, and increase proactivity.
Moreover, they decrease decision bias and are more objective than other approaches.
Above all, there's a simple fact: data does not lie. It helps to predict future trends and raise success chances.
Moreover, it also generates higher levels of revenue.
That's what makes Data-Driven analytics key for any business.
How To Develop a Data-Driven Mindset?
You now know what it is to be data-driven and why it matters.
But how can you work on developing a data-driven mindset?
We’ll give you some tips on this below.
- Data Literacy. Understand data to use it the right way! Use data visualization, develop new processes and provide staff training.
- Pattern Searching. Become more analytical and look for patterns to train your brain to become more Data-Driven.
- Biases Awareness. We all have our biases, and that’s ok! Being aware of them will help reduce their impact on the decision-making process.
- Failure Embracing. When you fail, please make the most of it and learn from your mistakes. They will provide valuable data that you can use for the next round.
- Skepticism Approaching. Being Data-Driven entails using data to answer questions. You cannot take every piece of information you receive at face value!
Why is Big Data important?
Big Data tools reduce storage costs and save time on data analysis.
For instance, the analyzed data translates to a better understanding of market conditions.
As a result, you'll be able to make good decisions faster.
Also, it helps to develop and market innovative products and services.
Other benefits include boosts in customer acquisition and retention.
Overall, we'd say big data is so important for many reasons.
Conclusion
As we’ve seen, Big Data applications and Data-Driven analytics have incredible potential.
Of course, they seem to be the future of businesses and Software Development.
But they will also provide wonderful opportunities to improve our quality of life.
We hope to have given you a broader perspective of big data and data-driven development.
What do you think they will bring us next?
