Big Data And Analytics Essay

Big data analytics can be used by company to make informed business decision by examining large amount of varied data to get customer preferences, market trends and other useful information. Company can use it to explore new revenue opportunities, improved operational efficiency, better customer service and competitive advantages over rivals.

The analysis of big data is the process of organizing, collection, analyze and examining the large volume of data to find patterns, market trends and useful information. This analysis helps organizations to better understanding about the information within data, and helps analyst to make better

Big data analysis is used in improving health. There are many health applications available on the smart phones from which we can analyses and improve our health. Also by gathering information from the electronic patient records, big data can provide a more appropriate understanding of the diseases and develop cheaper therapies.

The BI tool can be used to analyze and understand the business risk from all aspects of its operations, if implemented and maintained well, this tool will help bring attention to areas that need improvement. (Kapoor,2010).The BI tool can be customized with dashboards that can track all corporate functions like human resources, recruiting, operations, security, information technology, customer relationship management and many more departmental dashboards.

Heterogeneity, scale, timeliness, complexity, and privacy problems with Big Data impede progress at all phases of the pipeline that can create value from data. The problems start right away during data acquisition, when the data tsunami requires us to make decisions, currently in an ad hoc manner, about what data to keep and what to discard, and how to store what we keep reliably with the right metadata. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search: transforming such content into a structured format for later analysis is a major challenge. We will find out a way how structured big data can be transformed into unstructured data to increase the performance. Storage price trends have shown that now a days it’s not a big deal to afford storage for big un structured data. As far as performance is concerned, big data manageability in terms of unstructured data is more efficient. So as far as revenue is concerned this research will provide

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

Business Intelligence information consists of chronicled data, and additionally new information assembled from source frameworks as it is generated, empowering Business Intelligence supports multi-level decision making processes. Initially, Business Intelligence tools were essentially utilized by IT experts and data analysts whose job is to run analyses and generate reports with query results for business clients. Progressively, however, business administrators and workers are utilizing BI software themselves, on account of the advancement of self-administration of BI and data discovery tools

Big data analytics is the process of checking and handling large data sets which normally contains variety of data types. Through handling these data it helps to know the patterns and even the correlations which are not known. Handling of the large data sets also helps in knowing the market trends and even in knowing what the customers prefer. The information which these data analytics gives are important information for business. Most of the surveys which have been done have shown that big data analytics have revolutionized supply chain. Most companies and

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

Business analytics (BA) is a method combining skills, technologies, applications, and processes that is used by the company to gain valuable insight on the processes of the business by collecting statistical data. BA is used by the company to improve the business decisions and can be used to automate and optimize the business processes. A data driven company, such as SMB Computation treats their data as a corporate asset and uses it to gain a competitive advantage. For business analytics to be successful, skilled analysts who recognize the technologies and the companies, organizational guarantee to the data-driven decision-making must collect quality data (Rouse, 2010).

Business Intelligence is gaining popularity in many organizations and companies. Business Intelligence solutions are developed to help the organizations understand their customers, activities and performance. BI solutions act as measurements units for a business or an organization. Deficient intelligence leads to weak decision making. BI has

Big data and analytics are hot growth areas, not only for IT organizations, but for businesses across all industries.

Big Data is an outgrowth of the proliferation of databases and massive data sets. The insights needed to more intelligently manage an organization can be found in the myriad of data sets that comprise a Big Data platform. The greatest challenge of Big Data is contextual intelligence supported by integration to legacy, 3rd party and homegrown application systems located throughout an enterprise (Jacobs, 2009). To get ot his level of proficiency in analyzing Big Data sets and databases, enterprises need Business Intelligence (BI) and analytics tools that can parse through terabytes quickly, finding patterns and analyzing massive amounts of data, then distilling it down to key

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

‘Big Data’ is the application of specialized techniques and technologies to process very large sets of data. These data sets are often so large and complex that it becomes difficult to process using on-hand database management tools. There are several techniques which are widely used in implementation of Big Data.