The Dominating Trend Of Big Data Analytics: A Study

Data has become an integral part of human society. As we progress further into the 21st century, information technology, computer science, and networking have seeped into all aspects of an average human’s life and businesses of almost all scales. Companies across all sectors have realized the ubiquity of data opportunities. Be it an MSME in the food and beverages sector, a multinational B2B giant or a reputed online coursework writing service, businesses worldwide are fast integrating extensive data analytics infrastructure to use data to perform & operate. 

In this write-up, we will look into how data analytical thinking is the way forward, and the different forms of how big data analytics is helping companies & organizations reach new heights.

The Era of Big Data and Data Analysis

Most enterprises deal with vast volumes of data during their operations. With the right kind of infrastructure, most business aspects are open to data collection and subsequent processing, from operations, manufacturing, supply-chain management to consumer analyses, ad campaign performance and workflow procedures, etc. Many businesses such as an online coursework writing service access and use data from secondary sources, such as market trends, competitor’s actions, and news from the industry. 

As evident, data is all-pervasive and everywhere, with almost every operation generating one form of data or the other. It is its ubiquitous nature that makes it a critical factor in predictive analytics and inferring information. 

  • Marketers are studying data to predict customer behavior. From helping academic services determine the best assignment experts for a student to Netflix using data to serve better content to viewers, marketing, and data analytics lie at the heart of it all.
  • Gone are the days when a few statisticians could guide firms in exploring datasets. 

It’s the age of BIG DATA, the term used to describe the massive amounts of structured and unstructured data that companies handle nowadays. 

Consider the case of the world’s largest retailer, Walmart. 

Walmart uses big data to monitor and control its workflows and supply chains across all its outlets, stores, and e-commerce ventures. The company uses big data analytics to improve its pharmacies’ efficiency, gain better insights from customer feedback & optimize customer experience, better manage steps of their supply chain management, and more.

  • Data analytics is not just limited to business applications. Big data analytics fund widespread and critical applications in research and design, meteorology, testing, manufacturing, energy production, etc. 

Data mining and big data analytics allowed retail chains like Walmart to make the best use of the massive amounts of customer history and make accurate predictions about its stocks and inventories during emergency weather conditions. 

Coursework writing services analyze client data to delegate the perfect assignment expert that best suits a particular client’s requirements.

Similarly, meteorological centers are now employing analytical models to predict local weather patterns and global climate change. Weather satellites, balloons, and similar instruments gather and record scores of data, & data analysis models allow to obtain insightful knowledge. 

Besides the different applications stated above, it finds widespread usage in :

  1. Security 🡪 data encryption and security involves the processing of massive amounts of data
  2. Risk Detection 🡪 financial companies can take better decisions regarding sanctioning loans and perform better customer profiling.
  3. Stock Market Analyses 🡪 it is no surprise that data analytics finds extensive usage in making stock market predictions.
  4. Image and Speech Recognition 🡪 Smart bots such as Alexa, Cortana, and the like employ data analysis models to understand and learn from some input data. 

The manifold advantages of data science and analytics are the reasons behind its unprecedented rise and widespread implementation. 

The Biggest Benefits of Data Science

The rising popularity of data science is a direct consequence of the advantages it offers to data-driven organizations.

Here are some of the most significant benefits it offers. 

  1. Better business intelligence
  2. Targeted Marketing 
  3. Proactive and improved  customer service
  4. Manufacturing and providing customer-centric products & services
  5. Improving operational performance and efficiency
  6. Making accurate predictions about the market and forecasting trends

The increasing utilization of data science in businesses and organizations across sectors has led to the rise of several data analytics platforms capable of storing, processing, and analyzing big data. 

Now, let’s look at some of the most popular big data analytics engine of 2020. 

The Biggest Big Data Analytics Software Applications In 2020

Companies run big data analytics software platforms on large data sets gathered from big data clusters. These applications work on big data to dig out data trends, patterns, outliers, anomalies, etc., and synthesize insightful knowledge via easy to interact with user interfaces and detailed visualizations.

There are several big data analytics software applications out there today. Here are some of the most powerful data analysis engines used by organizations across several sectors.

  1. Qlik Sense = A platform for modern and self-service analytics to drive discovery and data literacy for any organization.
  2. Azure Databricks= The platform uses data science in a high-performance analytics platform to drive innovation and accelerate performance.
  3. MATLAB= One of the most popular programming, modeling, and simulation tools.
  4. Qubole= A data lake platform that allows for secure data operations such as machine learning, streaming, and ad-hoc analytics. 
  5. Google BigQuery= A low cost, scalable, serverless, and fully managed data warehousing for performing data analytics.
  6. Alteryx= A leader in self-service data analytics platform that allows users to prepare, blend, and analyze data using a repeatable workflow. 
  7. Azure Data Lake Analytics= Microsoft’s cloud-based and distributed data processing architecture in the Azure cloud.

These are some of the most popular and capable big data analytics platforms used by businesses, research organizations, and other ventures to do more with their data. Data analysis and big data lie at the heart of all of these software suites and drive innovation, growth & development across all sectors, like never before.

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