Piesakies studiju kursam “Data Management” par īpašu dalībnieka cenu!


Laika periodā no 2020. gada 14. maija līdz 7. jūnijam Banku augstskola piedāvā apmeklēt studiju kursu “Data Management” (angļu val.), kurš sadalīts 3 moduļos. Kursa un moduļu apraksts ir skatāms zemāk.

Interesentiem ir iespējams pieteikties gan uz visu kursu, gan atsevišķiem moduļiem. Lekcijas būs online, kā “hands-on sessions”, diskusija un praktiskais darbs non-stop.
Lektors – Elchin Jafarov

Lekciju laiki:

IV, V 18:00-19:30, 19:40-21:00

VI,VII 09:00-10:30, 10:40-12:10, 13:00-14:30, 14:40-16:10

1.modulis – Excel for Finance – 14/05/2020 – 17/05/2020

2.modulis – Management Information Systems – 28/05/2020 – 31/05/2020

3. modulis – Automation and Programming – 04/06/2020 – 07/06/2020

  • 1 moduļa cena 300 EUR 180 EUR;
  • Reģistrācijas maksa 20 EUR (piesakoties uzreiz uz vairāk nekā vienu moduli, papildus reģistrācijas maksas netiek piemērotas);
  • Maksa par visu studiju kursu 900 EUR 560 EUR (iekļaujot reģistrācijas maksu);
  • Norises vieta: Online;
  • Valoda – angļu.

Pieteikšanās –  E-pasts: Tatjana.Mavrenko@ba.lv

Data Management

Data is the oil of the contemporary generation. It became one of the most valuable assets, which companies possess. Like crude oil, it could be left “underground”, or simply burned in the furnace, bringing primitive value. But if data mined, processed and treated properly, it could bring a whole level of productivity and make billions of wealth, by fueling the new digital economy. Many leading companies are paying increasing attention and intensively investing capital into data technologies. Interestingly, even simple approaches to managing data can generate plenty of value for your business. How? We will master those in our series of course.

Management Information Systems

The course covers major digital trends in modern organization and elaborates on such buzzwords as Cloud, IoT, Artificial Intelligence, Machine Learning, SaaS, PaaS, IaaS, Big Data, ERP and others. We will concentrate on applied Data Analytics and Business Intelligence by overviewing and using the existing software and solutions for handling and practical usage of data. Our primary tools will be the Microsoft Power ecosystem, like Power Query, Power Pivot and Power BI (business intelligence).

Excel for finance

Simply more professional and efficient usage of Excel already can make your work with data enjoyable and considerably more valuable. The course will cover:

  • Addressing objects in Excel and working with objects
  • Data types, variables and arrays in Excel: solving the bugs in multiple Excel file environments
  • Data importing, PowerQuery and working with data.
  • Processing textual data
  • Working with date/time
  • Logic flow in Excel: beyond the simple IF
  • Wide and Long data
  • Data aggregation (with SUMMIFS/COUTIFS and advanced array formulas)
  • Data query using PowerQuery appends and merges
  • Advanced intelligence dashboards in Excel with slicers, table-relationships and advanced PoverPivot tables.

Power BI

Business intelligence requires powerful tools, and one of them is PowerBI. We will actively learn PowerBI functionality and apply it for creating measures and advanced analytics using DAX data analytics language.

  • Power BI interface
  • What can and cannot be done in Power BI
  • More on data extraction using PowerQuery
  • Data table relationships in Power BI
  • Creating calculated columns
  • Creating measures using DAX syntax
  • Advanced measures with iterators
  • Creating powerful dashboards
  • Using third party visuals

Automation with VBA and R coding

Boring daily routines with Excel? Visual Basic for Applications (VBA) solves that. In this course, we learn and apply basic coding, which helps you to delegate a lot of workflow to the computer.

VBA track

  • Excel DOM (Document object Model)
  • Learning to read the code: it is simple if you try
  • Writing our own procedures
  • Coding custom Excel functions
  • More on variables, arrays and data types
  • Loops and their usage
  • Program flow
  • Error handling