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Data Analytics and Technology

Original price was: $1,400.00.Current price is: $999.00.

Data is all around us. Data is the new raw material of the businesses. Companies need individuals who can transform data into information, and this requires analytical skills. With the boom in the use of analytics, having skills to deep dive into data to create insights is not just valuable, it is the necessity of the time. To identify new market opportunities for their products and services, companies need individuals who can use analytical skills to find hidden patterns in the data and can help to formulate business and marketing strategies. Data Analytics is a critical component of business performance and there are all sorts of new opportunities cropping up for talented individuals. The future belongs to those who see possibilities before they become obvious.

In this course you will learn:

1. Connect and collect data from diverse and dynamic data sources.
2. Cutting-edge techniques of data cleansing.
3. How to effectively structure and organize large datasets to conduct high quality analysis.
4. Build fully interactive dashboards with stunning visuals of Microsoft Power BI and share insights.
5. How to organize data within a database and manipulate it using Structured Query Language.
6. How to protect financial and nonfinancial data from cyber attacks.
7.Analyze big datasets and create analytics with Python.

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Description

Course Highlights

    • Data Analytics and Technology.
    • Importance of Data Analytics for Accountants.
    • Connect, collect, and clean your data.
    • Extract, Transform and Load.
    • Data Modelling and Evaluation
    • Calculated columns vs DAX measures.
    • Time Intelligence in Power Pivot
    • Conditional Measures
    • Iterators functions
    • Multiple Data Tables
    • Business Intelligence and Data Visualization
    • Power BI Desktop
    • Power BI Services
    • Power BI Mobile
    • Data Analytics in Auditing and Accounting
    • Database Management [Tables, Queries, Forms, Reports, Macros]
    • Data Mining with Structured Query Language
    • Cybersecurity
    • Analyzing Financial Data with Python