This week’s article provided a case study approach which highlights how businesses have integrated Big Data Analytics with their Business Intelligence to gain dominance within their respective industry.  Search the UC Library and/or Google Scholar for a “Fortune 1000” company that has been successful in this integration. Discuss the company, its approach to big data analytics with business intelligence, what they are doing right, what they are doing wrong, and how they can improve to be more successful in the implementation and maintenance of big data analytics with business intelligence. Your paper should meet the following requirements: • Be approximately 3-5 pages in length, not including the required cover page and reference page. • Follow APA guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion. • Support your response with the readings from the course and at least five peer-reviewed articles or scholarly journals to support your positions, claims, and observations. • Be clear with well-written, concise, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.

Title: Integration of Big Data Analytics with Business Intelligence in Fortune 1000 Companies

Introduction
In the era of digital transformation, businesses are increasingly relying on the integration of Big Data Analytics (BDA) with Business Intelligence (BI) to gain a competitive advantage within their respective industries. This paper examines a Fortune 1000 company that has successfully integrated BDA with BI, evaluates their approach, identifies areas for improvement, and proposes recommendations for enhanced implementation and maintenance.

Company Overview
Google, one of the leading technology companies in the world, serves as an exemplary Fortune 1000 company that has effectively integrated BDA with BI. With its vast array of products and services, including search engine, cloud computing, and advertising, Google generates an enormous amount of data, which it leverages to make data-driven strategic decisions.

Approach to BDA with BI
Google’s approach to BDA with BI involves leveraging its expertise in data management and analytics to generate actionable insights. The company utilizes various big data technologies and tools, such as Hadoop and Google Cloud Platform, to efficiently store, process, and analyze massive volumes of structured and unstructured data. This enables Google to gain valuable insights into customer behavior, market trends, and competition, and translates them into informed decisions that drive innovation and profitability.

What Google is Doing Right
Google’s success in integrating BDA with BI can be attributed to several factors. Firstly, the company has a robust data infrastructure and employs advanced analytics techniques that enable it to process and analyze complex data sets in real-time. Secondly, Google focuses on hiring and developing data scientists and analysts who possess the necessary skills to extract meaningful insights from the data. Thirdly, Google has a culture of data-driven decision-making, where decisions are based on empirical evidence rather than intuition, leading to greater efficiency and effectiveness.

Where Google Can Improve
Although Google has been successful in its integration of BDA with BI, there are areas where improvements can be made. Firstly, there is a need for better data governance practices to ensure data quality, consistency, and privacy. Despite its emphasis on data-driven decision-making, Google faced scrutiny and controversies regarding its handling of user data, necessitating stricter policies and procedures. Secondly, Google can enhance its predictive analytics capabilities by incorporating advanced machine learning algorithms, enabling the company to anticipate trends and customer needs. Lastly, while Google has invested heavily in data analytics, there is room for improvement in the visualization and communication of insights, as clear and intuitive data visualization aids decision-makers in understanding complex concepts effectively.

Recommendations for Improved Implementation and Maintenance
To enhance the implementation and maintenance of BDA with BI, Google should consider the following recommendations. Firstly, the company should establish a dedicated team responsible for data governance and compliance, ensuring adherence to data privacy regulations and industry best practices. Secondly, Google should invest in talent development programs to continuously upgrade the analytical skills of its workforce, including staying abreast of the latest tools and techniques in BDA. Lastly, Google should explore partnerships with leading visualization software vendors to leverage intuitive dashboards and visual analytics tools, facilitating the dissemination of insights throughout the organization.

Conclusion
Google serves as a prime example of a Fortune 1000 company that has effectively integrated BDA with BI, resulting in data-driven decision-making and business success. By leveraging its robust data infrastructure, investing in analytics expertise, and fostering a culture of data-driven decision-making, Google has demonstrated the power of BDA with BI in driving innovation and profitability. However, there is always room for improvement, and by focusing on data governance, predictive analytics, and enhanced visualization techniques, Google can further enhance its implementation and maintenance of BDA with BI.