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Big data analytics and businessLaajuus (5 cr)

Code: TT00CC74

Credits

5 op

Objective

The aim of the course is to give students basic knowledge and skills about the meaning and application of big data analytics in business. Students understand the role of big data analytics in decision-making and business development in different industries. In addition, the goal is to introduce students to practical applications and business cases related to big data analytics from various industries either on the basis of guest lecturers or roundtable webinars.

Content

Big data analytics refers to the strategies used by organizations to collect, organize and analyze large amounts of data to discover valuable business insights that would otherwise not be possible through traditional systems.

The course covers the following themes:

- Basics and concepts of big data analytics
- The role of big data analytics in business
- Application of big data analytics in different industries
- Ethical and legal perspectives
- Future trends and opportunities

Materials

The learning materials consist of the lecture materials distributed in the course, possible additional materials and resources found on the internet. At the beginning of the course, a more detailed list of recommended study materials and sources is distributed.

The course literature mainly consists of articles, reports and online materials related to the course themes. At the beginning of the course and as it progresses, a more detailed list of course literature will be distributed.

Assessment criteria, excellent (5)

The student provides strong evidence of skills and their development in the learning diary. The diary has a flawless style and content that is argumentative and insightful. In the learning diary, an entry has been verifiably added every week, the extent and level of content of which corresponds in terms of workload to the work according to the time use of the course. The source material has been critically evaluated and weighed.

Assessment criteria, good (3)

The student reflects or analyzes the development of his skills in his learning diary. The content of the learning diary is neat and clear, and the writing style is fluent and almost flawless. The work has sometimes been done either every other week or most weeks. The use of source material is systematic, clear to the reader, and the source material is versatile and appropriate.

Assessment criteria, satisfactory (1)

The student lists or applies basic skills in his learning diary. The content of the learning diary is unstructured or stylistically uneven. The learning diary has not been properly updated every week, but the most significant part of the work has been done in a week. A list of sources has been prepared, but there is little or no connection between the main text and the sources.

en
Enrollment

02.07.2025 - 31.07.2025

Timing

01.08.2025 - 31.12.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Jani Sourander
Groups
  • TTM23SAI
    TTM23SAI

Objective

The aim of the course is to give students basic knowledge and skills about the meaning and application of big data analytics in business. Students understand the role of big data analytics in decision-making and business development in different industries. In addition, the goal is to introduce students to practical applications and business cases related to big data analytics from various industries either on the basis of guest lecturers or roundtable webinars.

Content

Big data analytics refers to the strategies used by organizations to collect, organize and analyze large amounts of data to discover valuable business insights that would otherwise not be possible through traditional systems.

The course covers the following themes:

- Basics and concepts of big data analytics
- The role of big data analytics in business
- Application of big data analytics in different industries
- Ethical and legal perspectives
- Future trends and opportunities

Evaluation scale

0 - 5

Assessment criteria, excellent (5)

The student provides strong evidence of skills and their development in the learning diary. The diary has a flawless style and content that is argumentative and insightful. In the learning diary, an entry has been verifiably added every week, the extent and level of content of which corresponds in terms of workload to the work according to the time use of the course. The source material has been critically evaluated and weighed.

Assessment criteria, good (3)

The student reflects or analyzes the development of his skills in his learning diary. The content of the learning diary is neat and clear, and the writing style is fluent and almost flawless. The work has sometimes been done either every other week or most weeks. The use of source material is systematic, clear to the reader, and the source material is versatile and appropriate.

Assessment criteria, satisfactory (1)

The student lists or applies basic skills in his learning diary. The content of the learning diary is unstructured or stylistically uneven. The learning diary has not been properly updated every week, but the most significant part of the work has been done in a week. A list of sources has been prepared, but there is little or no connection between the main text and the sources.

Prerequisites

The course does not require previous knowledge. However, business knowledge and an understanding of data warehouses are useful.

en
Enrollment

19.08.2024 - 22.09.2024

Timing

01.08.2024 - 31.12.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Teachers
  • Jani Sourander
Groups
  • TTM22SAI
    TTM22SAI

Objective

The aim of the course is to give students basic knowledge and skills about the meaning and application of big data analytics in business. Students understand the role of big data analytics in decision-making and business development in different industries. In addition, the goal is to introduce students to practical applications and business cases related to big data analytics from various industries either on the basis of guest lecturers or roundtable webinars.

Content

Big data analytics refers to the strategies used by organizations to collect, organize and analyze large amounts of data to discover valuable business insights that would otherwise not be possible through traditional systems.

The course covers the following themes:

- Basics and concepts of big data analytics
- The role of big data analytics in business
- Application of big data analytics in different industries
- Ethical and legal perspectives
- Future trends and opportunities

Materials

Linkit oppimateriaaliin, mahdollisiin luentojen tallenteisiin sekä lukuvinkit löytyvät Reppu-alustan "Aloita tästä"-osiosta. Kurssin kannalta tärkein teos löytyy Alma Talent bisneskirjastosta. Tämä teos on: Listenmaa, J. *Laita tieto töihin: tiedolla johtamisen käsikirja* [e-kirja]. Helsinki: Alma Talent. 2023.

Teaching methods

Oppimispäiväkirja, luennot, vierailijaluennot (tai niiden tallenteet). Yhteisten luentojen tallennekäytäntö sovitaan kurssin alussa yhteisesti. Oppimispäiväkirja on laadittava Oppimispäiväkirja 101 -ohjeen mukaisesti käyttäen. Ohje sijaitsee osoitteesta: https://sourander.github.io/oat/

Kurssi on jaettu viikoittain kuuteen eri teemaan. Opiskelijat kirjoittavat teemojen aiheesta oppimispäiväkirjamerkinnän, noin 500-1000 sanaa, jonka avulla osoittavat osaamisensa. Useimmilla viikoilla on ulkopuolinen yritysvieras: luennot ovat monimuotoryhmän kalenterin mukaisesti (maanantai-)iltaisin. Vierailijaluennot taltioidaan, jotta opiskelijoilla on niihin pääsy, vaikka olisi estynyt tulemaan kyseiseen ajankohtaan paikalle.

Student workload

Luennoille osallitumisen tai niiden tallenteiden katsomisen lisäksi opiskelijan oletetaan käyttävän viikoittain kurssin laajuutta vastaava määrä tunteja tehtävien tekemiseen, itsensä kehittämiseen ja tämän prosessin dokumentointiin oppimispäiväkirjamuodossa.

Evaluation scale

0 - 5

Assessment criteria, excellent (5)

The student provides strong evidence of skills and their development in the learning diary. The diary has a flawless style and content that is argumentative and insightful. In the learning diary, an entry has been verifiably added every week, the extent and level of content of which corresponds in terms of workload to the work according to the time use of the course. The source material has been critically evaluated and weighed.

Assessment criteria, good (3)

The student reflects or analyzes the development of his skills in his learning diary. The content of the learning diary is neat and clear, and the writing style is fluent and almost flawless. The work has sometimes been done either every other week or most weeks. The use of source material is systematic, clear to the reader, and the source material is versatile and appropriate.

Assessment criteria, satisfactory (1)

The student lists or applies basic skills in his learning diary. The content of the learning diary is unstructured or stylistically uneven. The learning diary has not been properly updated every week, but the most significant part of the work has been done in a week. A list of sources has been prepared, but there is little or no connection between the main text and the sources.

Assessment criteria, excellent (5)

Opiskelija todistaa vahvaa näyttöä taidoista ja niiden kehittymisestä oppimispäiväkirjassaan. Päiväkirja on virheetöntä asiatyyliä ja sisälllöltään argumentoiva sekä oivaltava. Oppimispäiväkirjaan on todistettavasti lisätty viikoittain merkintä, jonka sisällön laajuus ja taso vastaa työmäärältään kurssin ajankäytön mukaista työtä. Lähdeaineisto on kriittisesti arvioitu ja punnittu.

Toteutuksen arviointikriteerit, hyvä (3-4)

Opiskelija reflektoi tai analysoi taitojensa kehittymistä oppimispäiväkirjassaan. Oppimispäiväkirjan asiasisältö on huoliteltua ja selkeää tai sujuvaa ja lähes virheetöntä asiatyyliä. Työtä on tehty välillä joko toinen viikko tai useimpina viikkoina. Lähdeaineiston käyttö on systemaattista, lukijalle selkeää ja lähdeaineisto on monipuolista sekä tarkoituksenmukaista.

Assessment criteria, satisfactory (1)

Opiskelija listaa tai soveltaa perustaitoja oppimispäiväkirjassaan. Oppimispäiväkirjan asiasisältö on jäsentymätöntä tai tyylillisesti epätasaista. Oppimispäiväkirjaa ei ole päivitetty asianmukaisesti viikoittain vaan merkittävin osa työstä on tehty viikossa. Lähdeluettelo on laadittu, mutta runkotekstin ja lähteiden yhteys on vähäinen tai olematon.

Prerequisites

The course does not require previous knowledge. However, business knowledge and an understanding of data warehouses are useful.

en
Enrollment

19.08.2024 - 22.09.2024

Timing

01.08.2024 - 31.12.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Teknologia

Teaching languages
  • Finnish
Degree programmes
  • Bachelor’s Degree in Information and Communication Technology
Teachers
  • Jani Sourander
Groups
  • TTV22SAI
    TTV22SAI

Objective

The aim of the course is to give students basic knowledge and skills about the meaning and application of big data analytics in business. Students understand the role of big data analytics in decision-making and business development in different industries. In addition, the goal is to introduce students to practical applications and business cases related to big data analytics from various industries either on the basis of guest lecturers or roundtable webinars.

Content

Big data analytics refers to the strategies used by organizations to collect, organize and analyze large amounts of data to discover valuable business insights that would otherwise not be possible through traditional systems.

The course covers the following themes:

- Basics and concepts of big data analytics
- The role of big data analytics in business
- Application of big data analytics in different industries
- Ethical and legal perspectives
- Future trends and opportunities

Materials

Linkit oppimateriaaliin, mahdollisiin luentojen tallenteisiin sekä lukuvinkit löytyvät Reppu-alustan "Aloita tästä"-osiosta. Kurssin kannalta tärkein teos löytyy Alma Talent bisneskirjastosta. Tämä teos on: Listenmaa, J. *Laita tieto töihin: tiedolla johtamisen käsikirja* [e-kirja]. Helsinki: Alma Talent. 2023.

Teaching methods

Oppimispäiväkirja, lähiluennot, vierailijaluennot tai niiden tallenteet. Oppimispäiväkirja on laadittava Oppimispäiväkirja 101 -ohjeen mukaisesti käyttäen. Ohje sijaitsee osoitteesta: https://sourander.github.io/oat/

Kurssi on jaettu viikoittain kuuteen eri teemaan. Opiskelijat kirjoittavat teemojen aiheesta oppimispäiväkirjamerkinnän, noin 500-1000 sanaa, jonka avulla osoittavat osaamisensa. Useimmilla viikoilla on ulkopuolinen yritysvieras: luennot ovat monimuotoryhmän kalenterin mukaisesti (maanantai-)iltaisin. Vierailijaluennot taltioidaan, jotta opiskelijoilla on niihin pääsy, vaikka olisi estynyt tulemaan kyseiseen ajankohtaan paikalle.

Completion alternatives

Ota yhteyttä opettajaan.

Student workload

Luennoille osallitumisen tai niiden tallenteiden katsomisen lisäksi opiskelijan oletetaan käyttävän viikoittain kurssin laajuutta vastaava määrä tunteja tehtävien tekemiseen, itsensä kehittämiseen ja tämän prosessin dokumentointiin oppimispäiväkirjamuodossa.

Evaluation scale

0 - 5

Assessment criteria, excellent (5)

The student provides strong evidence of skills and their development in the learning diary. The diary has a flawless style and content that is argumentative and insightful. In the learning diary, an entry has been verifiably added every week, the extent and level of content of which corresponds in terms of workload to the work according to the time use of the course. The source material has been critically evaluated and weighed.

Assessment criteria, good (3)

The student reflects or analyzes the development of his skills in his learning diary. The content of the learning diary is neat and clear, and the writing style is fluent and almost flawless. The work has sometimes been done either every other week or most weeks. The use of source material is systematic, clear to the reader, and the source material is versatile and appropriate.

Assessment criteria, satisfactory (1)

The student lists or applies basic skills in his learning diary. The content of the learning diary is unstructured or stylistically uneven. The learning diary has not been properly updated every week, but the most significant part of the work has been done in a week. A list of sources has been prepared, but there is little or no connection between the main text and the sources.

Assessment criteria, excellent (5)

Opiskelija todistaa vahvaa näyttöä taidoista ja niiden kehittymisestä oppimispäiväkirjassaan. Päiväkirja on virheetöntä asiatyyliä ja sisälllöltään argumentoiva sekä oivaltava. Oppimispäiväkirjaan on todistettavasti lisätty viikoittain merkintä, jonka sisällön laajuus ja taso vastaa työmäärältään kurssin ajankäytön mukaista työtä. Lähdeaineisto on kriittisesti arvioitu ja punnittu.

Toteutuksen arviointikriteerit, hyvä (3-4)

Opiskelija reflektoi tai analysoi taitojensa kehittymistä oppimispäiväkirjassaan. Oppimispäiväkirjan asiasisältö on huoliteltua ja selkeää tai sujuvaa ja lähes virheetöntä asiatyyliä. Työtä on tehty välillä joko toinen viikko tai useimpina viikkoina. Lähdeaineiston käyttö on systemaattista, lukijalle selkeää ja lähdeaineisto on monipuolista sekä tarkoituksenmukaista.

Assessment criteria, satisfactory (1)

Opiskelija listaa tai soveltaa perustaitoja oppimispäiväkirjassaan. Oppimispäiväkirjan asiasisältö on jäsentymätöntä tai tyylillisesti epätasaista. Oppimispäiväkirjaa ei ole päivitetty asianmukaisesti viikoittain vaan merkittävin osa työstä on tehty viikossa. Lähdeluettelo on laadittu, mutta runkotekstin ja lähteiden yhteys on vähäinen tai olematon.

Prerequisites

The course does not require previous knowledge. However, business knowledge and an understanding of data warehouses are useful.