What is Big Data Analytics and Why is it Important?

What is Big Data Analytics and why is it Important?

Big Data Analytics is the most happening thing in the world of business today! It is nothing but a form of advanced analytics, which helps organisations to harness their data and use it to identify new opportunities. Smarter business strategies, higher profits, more efficient operations and happier customers are the end results of using Big data analytics!

Cedar Software Technologies, a top-notch PHP web development company in Kochi, helps you to discover Big Data Analytics and its importance with this overview.

Why is Big Data Analytics important?

Big data analytics creates value! Many businesses can use big data analytics systems and software to make data-driven decisions that can improve business growth and profits. This leads to more effective marketing and improved operational efficiency of the business. Big Data Analytics can also create new customer personalisation easily and increase revenue opportunities.

The analytics process often involves the complex process of scrutinising big data like hidden patterns, correlations, market trends and customer preferences to uncover information.

How does big data analytics work?

Extensive volumes of structured transaction data and other forms of data not used by conventional BI and analytics programs are collected, processed, cleaned and analysed here. Many people like data scientists, statisticians, predictive modelers, data analysts and other analytics professionals work on this data.

Data preparation process steps:

Data Collection

A mix of semi-structured and unstructured data is collected by Data professionals from diverse sources like:

  • Web server logs
  • Social media content
  • Mobile phone records
  • Internet clickstream data
  • Text from customer emails and survey responses
  • Cloud applications
  • Mobile applications
  • Machine data captured by sensors connected to the internet of things (IoT)

Data is processed

After data is collected and stored in a data warehouse or data lake, data professionals must organize, configure and partition the data properly for analytical queries. Thorough data processing makes for higher performance from analytical queries.

Data is cleansed for quality

Data professionals scrub the data using scripting tools or enterprise software. They look for any errors or inconsistencies, such as duplications or formatting mistakes, and organize and tidy up the data.

Data Analysis with software

The collected, processed and cleaned data is analysed with analytics software. This includes tools for:

  • Data mining – sifts through data sets searching out patterns and relationships
  • Predictive analytics – builds models to forecast customer behavior and future developments
  • Machine learning – taps algorithms to analyze large data sets
  • Deep learning – a more advanced offshoot of machine learning
  • Text mining & statistical analysis software
  • Artificial intelligence (AI)
  • Mainstream business intelligence software

For storing large amounts of data, Hadoop and cloud-based analytics are Big data technologies that bring on significant cost savings. Faster, better decision making is possible based on the analysis. New products and services can be built with the ability to measure customer needs and satisfaction through analytics.

Many best IT companies in Kochi help businesses to use Big Data Analytics for their business growth. Contact us today to know more.

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