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Self Service Stream Data Analytics Platform


Call By Rıza

About Project

"Let Us Be Your Third Eye"


In this project, the aim is to develop a software for streaming data analytics. The input to the software is a set of streaming data resources. The software provides a set of functionalities including statistical analysis, such as counting, aggregating and predictive analytics/data mining functionalities on the streaming data.

The contribution of the project is basically due to analytics capability. The idea is to provide a set of functionalities common for different types of streaming data, and to design/develop an expansible environment with user defined functionalities.

The end-product is a web software involving a server module.

The project is designed for specifically two different data resources, text & numerical based data. Twitter and Yahoo Finance are selected as data providers. However, data sources can be extended as one wants.


What are the abilities of the software?

  • Analyzing tweets related to keywords provided by users. Results can be seen as bar chart, tag cloud, heat map and pie chart.
  • Retrieving various parameters of selected companies and present analyzed results on charts.
  • Future prediction of stock prices by linear regression model. The software can illustrate corelation between Twitter and Finance with user selection.
  • Project Video

    METU Engineering Day Design Project Winner


    RosetteSelf Service Stream Data Analytics Platform got the second place in METU Engineering Day

    Frequently Asked Questions

    Frequently asked questions about the project

    This project aims to provide a set of functionalities common for different types of streaming data, and to design/develop an expansible environment with user defined functionalities.

    There are several projects and tools on Big Data for real time analysis. However, most of these solutions focus on a specific data domain. Therefore, there is a need for generic software that is capable of processing various data domains in real time. Our aim is to fulfill this need by creating a library and a platform for self service data analytics on streaming data.

    Twitter is the text base source and Yahoo Finance is the numerical source of the our project, but our project supports other sources if they are text base or numerical.

    On the stream data, after analyzing we only keep the results in database. We do not store any private data about the user.

    Project Members

    Pınar Karagöz

    Assoc. Prof. Dr. Pınar KARAGÖZ

    Assoc. Prof. at METU Computer Engineering Department

    Interest Areas:

  • Workflow Systems
  • Database Management Systems
  • Data Mining
  • Logic Programming
  • Pınar KARAGÖZ

    Supervisor
    Ahmet Süreyya Rifaioğlu

    Ahmet Süreyya RİFAİOĞLU

    Teaching Assistant at METU Computer Engineering Department

    Interest Areas:

  • Artificial Intelligence
  • Data Mining
  • Ahmet Süreyya RİFAİOĞLU

    Team Leader
    Mustafa Ağrıman

    Mustafa AĞRIMAN

    Senior Undergraduate Student at METU Computer Engineering Department

    Interest Areas:

  • Mobile Application
  • Game Development
  • Playing Guitar
  • Mustafa AĞRIMAN

    Developer
    Buğra Kaan Demirdöver

    Buğra Kaan DEMİRDÖVER

    Senior Undergraduate Student at METU Computer Engineering Department

    Interest Areas:

  • Game Development
  • Playing Chess
  • Buğra Kaan DEMİRDÖVER

    Developer
    Şevki Onur Henden

    Şevki Onur HENDEN

    Senior Undergraduate Student at METU Computer Engineering Department

    Interest Areas:

  • Bioinformatics
  • Photography
  • Fishing
  • Şevki Onur HENDEN

    Developer
    Recep Fırat Çekinel

    Recep Fırat ÇEKİNEL

    Senior Undergraduate Student at METU Computer Engineering Department

    Interest Areas:

  • Database Management
  • Machine Learning
  • Big Data
  • Recep Fırat ÇEKİNEL

    Developer

    Which technologies we are using for this project?


    Apache Storm Apache Spark Cassandra Django Twitter4J Yahoo Finance

    Apache Storm Apache Storm Apache Storm