The emergence of the Internet of Things (IoT) in the recent decades coupled with automation of business processes, proliferation of social media and rise in e-commerce has led to reliance on ‘big data’ for business decision making. Big data refers to the vast amount of structured and unstructured data that inundates businesses and organizations on a daily basis. Big data is characterized by 5Vs including volume, velocity, variety, veracity and value.
- Volume: Big data typically involves large volumes of data that traditional data processing applications might struggle to manage. This includes data from various sources such as social media, sensors, devices, and business applications.
- Velocity: Data streams in at an unprecedented speed, requiring real-time processing to extract valuable insights. This is particularly relevant in fields like finance, telecommunications, and online retail, where split-second decisions can be crucial.
- Variety: Big data comes in various formats, including structured data (like databases and spreadsheets) and unstructured data (like text, images, videos, and social media posts). Managing and analyzing this diverse range of data types presents significant challenges.
- Veracity: This refers to the quality of the data. Big data sources may contain inconsistencies, errors, or noise, which can affect the accuracy and reliability of analyses and insights.
- Value: Ultimately, the goal of big data is to extract value and actionable insights from the massive amount of data available. This can involve analyzing patterns, trends, and correlations to make informed decisions, improve processes, or gain a competitive advantage.
Business Data Analytics (BDA)- KASNEB
To harness the power of big data, organizations often employ advanced analytics techniques, such as machine learning, data mining, natural language processing, and predictive analytics. Therefore, students must be competent in BDA.
Unit Description
- Recommended tool: Excel, R
- Unit Description: Enables candidates to use information technology to support decision making through business analytics.
- Prerequisite: Knowledge in Qualitative Analysis (QA), Financial Accounting and Reporting (FA&R) and Management Accounting (MA), Tax, Auditing and Public Financial Management.
Note: BDA is tested in a controlled computerized environment thus a candidate needs a laptop.
- Learning outcomes:
- Discuss fundamental aspects of big data and data analytics using CRISP (Cross industry standard process for data mining).
- Use data analytics for financial reporting, financial
Note: RCM Online College recommends taking Excel and Advanced Excel short course before enrolling for BDA. The college offers this course for pocket friendly rate of only KSHS 1850.
Here is a sample of excel short courses lecturers
https://www.youtube.com/watch?v=bCWw9-0_r2E
- Apply data analytics in financial management principles
- Apply data analytics in management accounting
- Apply data analytics in auditing techniques
- Apply data analytics in estimating
RCM Online College – BDA (KASNEB)
RCM Online College has a highly competent team of lecturers with vast knowledge and experience with BDA course material and exams. The college offers Business Data Analysis for a pocket friendly rate of only KSHS 9000. Enroll today for the MAY- August 2024 semester. The opening date at RCM Online College is 2nd May 2024.
Note: DO NOT wait for exam results to enroll for BDA because you will miss out on more than one month of the lecturers. Given that KASNEB has changed its exam setting style candidates require adequate time to ensure ease of assimilation of course content and familiarization with exam material. Pay a commitment fee of only KSHS 1200 to enroll. Upon receipt of the January -April exam results students that do not qualify for BDA will transfer the commitment fee to other classes that they need to retake.
Here is a sample of BDA courses lecturers
https://www.youtube.com/watch?v=YnkN9lV9kWQ&pp=ygULcmNtIGNvbGxlZ2U%3D
Visit our website at https://www.rcmonlinecollege.co.ke/, email us at [email protected], call us at +254719525000, or visit us at Stanbank House, 1st floor along Moi Avenue, Nairobi for clarification