What is big data technology? List of some important big data project ideas for final year students. The notable technologies in big data mean the functions of data extraction, data processing, and data analysis using the software tools and the functions of big data is the challenging task when the traditional data management tools are used in large data sets.

What is the big data life cycle?

The life cycle of data includes the categorization of various phases initially the specific unit of data is formulated for its production process and in addition, it undergoes the obliteration process at the completion stage. Even though, it is useful to differentiate the specification of the experts in data management.

What is a project kickoff?

The lifecycle of a project has various stages in that the project kickoff is the first and foremost stage. The project kickoff is a significant and challenging task that includes the organization of client and team members based on the communication, teamwork, and potential in the project.

Why does the project kickoff matter?

• The project kickoff requires an in-depth research analysis based on the project due to this research analysis and study the researcher will come out with significant insights about the projects
• The detailed study is essential for the research project management

Steps to a successful project ideas kickoff

• Recognize the project vision and mission
• Organize the best research team
• Outline the accurate key performance indicators (KPIs)
• Research methodologies and tools
• Kickoff discussion and planning
• Project kickoff association

Our technical professionals have years of experience in dealing with big data research and development. So, we have a complete awareness of all recent research trends that are currently present in this field. For the sample, we have listed down a few important components in big data project ideas for final year.

What are the main components of big data?

• • Data source
  • Data Analytics
  • Data management
• Data Analytics
  • The technologies which deal with statistical analysis and data mining denote the data analytics
  • In data analytics, the challenging task is the selection of an analytical solution and processing model and it is based on the domains such as
    • Production management
    • Emergency management
    • Efficiency of energy
    • E-government
    • Market Intelligence
    • E-commerce
    • Healthcare
  • Regression, an overtone of rule mining, vector machines, and decision trees are the machine learning techniques used in the data analytics process
  • The analytical services such as network, web, mobile, and text are used in the process of data analytics solution
• Data management
  • The massive amount of data is available from the sources such as IoT sensors, social media, weblogs, etc.
  • The challenges of data management includes the process of selection, storage, combination, and analysis
  • The data analytics includes the process of data based on the required scalability and diversity
  • The data acquisition takes place through the real-time data streams along with the various automated process
  • It is used to develop the quality assessment approaches and big data methods
  • The system has many quality issues due to its extensive accessibility
• Data source
  • The layers of data sources are collected with public and private data sources based on the latest data ecosystem
  • The external data are offered from the third parties and partners and in addition, the corporate data initiates the cloud system and internal system
  • The public data sources such as
    • Audios
      • examples of podcasts such as Twitter, Instagram, trends on Google, etc.
    • Videos
    • Conversations
    • Statistics
    • Images
  • It is used to offer the on-demand perceptions and data in real-time which is used to analyze the user interactions, etc.

Using semantics in the big data processing

• Availability variations
  • The continuous data accession from the intermediate forms, traffic cameras, etc. in addition, the satellite is considered as the region of interest
• Semantic variety
  • It is based on the terms which are used to measure the data which are interpreted and operated. For example, high salary may vary among the service in the united states and the service in Ethiopia
• Media variety
  • It is based on the data delivered medium. The difference between the transcript speech and audio speech is the example the similar data from various medium
• Structural variety
  • It is called the data representation such as the difference between the storage of tweets produced by the web and the format of the satellite image

How do I choose a project?

• Recognize the success parameters
• Resource evaluation
• Categorization of project champion
• Certify the project alignment with the organizational strategy
• Assessment based on the execution

What about agile project kickoffs?

Agile methodologies are used to accompany the value of project kickoffs with numerous agile questions. If the process went correctly, the agile project kickoff was used to enhance the assessment and clear viewpoint to the research team using the scrum, one of the significant agile methodologies.

The functions of agile project kickoff are similar to the functions of big data project ideas for final year students to kickoff such as

• View of the initial process
• Recognize the related points about projects
• The function of the project
• Get to know victor’s project
• Organize the general requirements
• Proper teamwork