Skip to main content

What is Big Data Analytics-Introduction


Big Data Analytics-Introduction
What is Big data Analytics?
Big data refer to a term that describes the volume of data like data processing application software which has both structured and unstructured to deal with challenges like capture, search, storage, analysis, data curation, sharing, visualization, transfer, querying, updating and information privacy that inundates a business on a day-to-day basis. It is not important the amount of data, but it what companies do with these data. It can be analyzed for insisted that is going to lead better decision and strategy.
The main components of big data as follows.

  • Techniques for analyzing data, such as  machine learning, A/B testing, and natural language processing
  • Big data technologies, like databases, business intelligence, and cloud computing.
  • Visualization, such as graphs, charts, and any displays of the data.
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Big data examination is the way toward looking at extensive and changed detail indexes like Big data  to reveal concealed examples, obscure relationships, showcase patterns, client inclinations and other valuable data that can help associations settle on more-educated business choices.

For more information on Analytics and Big Data, please visit http://olgaazina.blogspot.com/2017/04/status-and-future-of-big-data-part-3.html

Comments

Post a Comment

Popular posts from this blog

Significant travel and leisure company uses analytics to drive customer acquisition

​  Leisure company uses analytics to drive customer acquisition Today’s technology allows businesses to collect ever-growing piles of customer and prospect transaction, demographic, and preference data. But more information does not mean more insights. Analytics is a powerful tool that aims to help organizations to find   opportunities to improve marketing, sales, and customer service . I read about topic in business analytics is that a great travel and entertainment company were searching for ways to raise its acquisition of co-branded credit card customers and the old strategy of daily email was leading to low yields and high opt-outs. They used an analytics techniques to identify the most likely customers to accept deals, using a mix of both internal and external data. Also, the company created machine learning algorithms to predict deals and offers acceptance rates by segment, going on to prioritize media usage, frequency, messages,   and timing. The aim wh...
1 comment
Read more

What is Big Data Analytics -Conclusion

Big Data Analytics -Conclusion Big Data improves transportation and energy consumption in the city, making our favorite websites and social networks more effective and even preventing suicide. Companies collect more data than they know what to do. Big Data is everywhere; The volume of data produced, stored and mined is incredible. Today, companies use data collection and analysis to develop more coherent business strategies. Factory use the data obtained from the use of the actual products to improve and develop new products and create innovative offers after-sales services. This will continue to be a new area for all industries. Data has become a competitive advantage and a necessary part of product development. Businesses succeed in great time data not only because they have more or better data but because they have good teams that set clear goals and define success that seems to ask the right questions. Big Data creates new growth opportunities and new business cate...
3 comments
Read more

Data Monetization strategy in Business  - conclusion

Data Monetization strategy in Business   Data monetization is all about selling the data which in turn is about revealing certain characteristics .It depends on how individual company approaches the concept to the data monetization no matter the company or their individual approach.An organization can play only one role in data monetization. It can either be a consumer of the data, an aggregator of the data or the creator of the new data. By understanding which role fits the organization best, one will be able to find the ways to monetize the data. Finally,Every company will approach data monetization differently, but gathering a variety of ideas from academia, tech analysts, and leading practitioners. Data monetization can be about selling data. Most of the time, monetization is less direct: making a process run more efficiently, incentivizing certain types of behavior, or revealing the true value of an asset. It is increasingly becoming a signif...
2 comments
Read more