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enterprise software developmententerprise software development

Big data is a method that refers to the management and processing of a large volume of data that is too large and complex to be treated in a traditional way. This involves the extraction of valuable information from large volumes of data using specialized software development solutions and tools. This is why Big Data is of great interest for companies.

Big Data is characterized by its “3Vs”: volume, speed and variety . Big Data for companies is interesting for its ability to analyze a large volume of different data and relate them in a very short time. But how does Big Data work?

First, a large amount of data is collected from various sources, such as social networks, sensors, commercial transactions, etc. This data is then stored in distributed systems such as Apache Hadoop that allow parallel processing.

Once stored, processing and analysis software such as Spark is used, extracting the relevant information. Finally, the time of analysis would come, the data is interpreted and decisions are made based on the patterns identified in the data. In short, it is a process composed of large-scale data acquisition, storage, processing and analysis that offers valuable insights.

Success stories of Big data in companies:

Zara:

Zara is the largest clothing distributor in the world. Its main secret during the last decade has been efficient use of information thanks to Big Data. Thanks to Big Data, companies like Zara can detect new trends quickly and satisfy customer demands in record time.

Some of the examples of how they have implemented Big Data are:

Innovation and user experience: Zara has multiplied its size in ten years thanks to its focus on custom enterprise software development and customer experience. This is why it is capable of adapting to new market demands and offering a coherent shopping experience to the user. You just have to look at how from time to time they change the structure of both their physical store and their online store.

Real-time data analysis : Zara’s design teams conduct daily reports on sales and products to adjust supply to public demand. This leads them to renew their collections every two weeks, much faster than their competition.

Efficient supply chain – The close relationship you have with your suppliers and your data analysis allows you to create flexible and accurate planning.

Information control : thanks to efficient use of the large volume of data they have available, (from orders to sales trends) it allows them to launch around 18,000 new references each year.

Netflix:

Another of the most frequent uses of Big data in companies is carried out by Netflix. Its focus is on content personalization . Approximately 80% of views come from highly personalized recommendations, derived from analysis of searches and user preferences. In addition, the platform uses Big Data for production, making decisions based on predictive analysis that range from the choice of actors to the ideal launch time.

The constant improvement of the user experience is another highlight. Netflix adapts its platform with around 40 million versions to satisfy various tastes and viewing habits. Optimizing content delivery is possible thanks to detailed analysis of devices used and consumption patterns. Improving the accessibility of movies according to user preferences and optimizing the efficiency of the service.

Amazon:

Amazon stands out in the use of Big Data by being one of the pioneers in using it in the purchasing experience. Its main successes were:

Shopping Predictions:

  Use predictive analytics to provide personalized recommendations. These recommendations are based on purchase history, pages visited and comments, improving the relevance of the suggestions.

Personalized Experience:

  As we have seen previously, this offers each user a unique experience adapted to their needs. To do this, it uses business intelligence and analysis of large volumes of data.

Continuous Innovation:

  Encourage constant innovation, using Big Data to understand customers and adapt products and services to their changing tastes

Machine Learning:

  Applies machine learning to analyze and learn from large data sets. The consequence of this is the continuous improvement of operational efficiency and customer satisfaction.

PepsiCo:

Through big data and analytics in the cloud, Pep Worx, PepsiCo strategically optimizes its market presence. By advising stores on what products to buy, their ideal location and appropriate promotions, the company maximizes its impact. Below is an example of how Big Data in companies should be used.

At the launch of their “Quaker Overnight Oats” product, they identified 24 million specific households to target their product. To do this, they determined the most likely purchasing places for these audiences. By creating promotions tailored to these specific areas, they achieved a remarkable 80% growth in product sales during the first 12 months after launch. This focused data approach demonstrates the power of personalization in product success.

Conclusion

In conclusion, Big Data has transformed the way software development consulting firms operate and make decisions. From giants like Zara and Amazon to entertainment platforms like Netflix and consumer companies like PepsiCo. The strategic use of Big Data has demonstrated its significant impact.

From personalizing the customer experience and improving operational efficiency to anticipating market trends. The use of Big Data in companies like these has helped them succeed in staying at the forefront of their respective industries. Are you already using Big Data in your company? Contact us and start using Big Data combined with Artificial Intelligence. Start multiplying your results.

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By Pranay Aduvala

Pranay is a software engineer and tech writer with a passion for digital marketing. Combining technical expertise with marketing insights, He write's engaging content on topics like Technology, AI, and digital strategies. With hands-on experience in coding and marketing, Connect with him on LinkedIn for more insights and collaboration opportunities:

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