Business Intelligence and Analytics

Today, Business Intelligence, Business Analytics and Big Data issues are among those given top priority by all companies and which play a significant role in determining the strategies and decision-making processes. In the most basic definition, Business Intelligence is the sum of all the methodologies, theories, software and processes used by a company to turn raw data into meaningful information and reports through analysis. Big Data is the form of non-structural data, in other words data collected from different sources such as social media posts and sharing, sensors, photographs, videos, voices and log files that has been converted into a form which is meaningful, processable and reportable.

Big data continues to grow at unprecedented and unpredictable levels, as IoT has found increasing avenues of use. It is not possible to store and process data at this size in contemporary relational databases or to store data in standard data storage structures. Today, many companies continue to make decisions based on information they obtain through classical data warehousing and data mining methods. However, the form of data has changed in form. In 2011, 100,000 Tweets were tweeted and 3,600 photos were shared on Instagram per minute, while in 2016 400,000 Tweets are tweeted and 43,000 photos are shared on Instagram every minute. These rates indicate that photo loading rate has grown 12 times in 5 years. This is a very significant change.

Business Intelligence solutions is a discipline turned to by companies for the fastest and most correct decision-making in processes such as improving business processes, defining new business opportunities, reducing costs, planning and budget control.

Despite being widely utilized in restaurant chains and retail merchandising, Business Intelligence solutions are actually used, indeed necessary, in all industries.

 

Finance Industry:

It is intensively used by companies operating in the finance sector, such as banking, stock exchange and insurance, to correctly analyze customer trends, create products suitable for customers, determine the direction of financial investment, accelerate processes and eliminate problems.

The business intelligence interpretation of big data analysis can be extremely effective in user customization of internet banking and ATMs. Creating end-user interfaces, providing reminders to customers and offering personal banking campaigns have become very common, especially according to the most frequently performed transactions during the day by customers using internet banking and ATMs.

 

General Industry:

It used to ensure optimization as well as the fastest and most correct decision-making in all business processes such as production, sales and marketing, including retail merchandising, wholesale merchandising and restaurant chains; for competitor product analysis, consumer trend analyses, supply optimization, costing and budgeting, and also in all processes such as storage and retention by companies operating either as sole-proprietorships or on the corporate scale.

Healthcare Industry:

It is used in creating healthcare products and processes, such as decision-making, for budgeting and investment studies to offer future services by blending structured individual data, and unstructured data such as ultrasound and x-ray, so as to offer the most effective customized medical service to patients. Also, the databases created for many researches in the pharmaceutical industry are continuously kept open for the access of researchers.

 

 

Sports and Entertainment Industry:

In the sports and entertainment industry, the IoT is especially used in areas such as ticketing operations, determining locations and timing, directing and identifying end-user perceptions, fan and loyalty management and creating blacklists and whitelists by blending unstructured data from passage control systems and CCTV, with structural data such as identity information.

 

Public Security:

It processes the information of citizens and provides a continuous online service for many government services such as Criminal Record Inquiries, 4A Service Listings, Court Case Inquiries, UYAP Entries, IMEI Services, Workers Unions Transactions, R&D Incentives and Application Inquiries, Tender Inquiries, Vehicle Inquiries and e-Passport Dispatch tracking.

 

Energy Industry:

It stores and processes data related to subscribers’ individual usage received from smart meters and networks. Processes such as energy supply and demand, investment locations, energy price tariffs, outages and maintenance work are managed based on this data.

Telecommunication Industry:

It is used in many processes such as network capacity planning based on the map data of subscribers’ access points and determining the point where the highest number of advertisements are to be placed based on social media sharing, creating cross-marketing campaigns in regions with dense human populations based on tweets in industries such as tourism that are influenced by seasonal changes, determining the most accessed websites from the DNS access records of users and creating infrastructure plans as well as creating product and service campaigns.

Netas creates the most appropriate data model for customers by primarily offering a free of charge discovery service and analyzing their structures. Then, flexible solutions meeting the changing dynamics and needs of our customers are offered, especially consultancy and resource leasing services. The situation we most frequently encounter with our customers is the lack of resources required for compliance with project plans. In such cases, we provide the necessary support and resources to our customers to ensure they duly complete their projects.

Basic services Netas provides in this regard:

  • Preliminary Analysis Service (Free of charge)
  • Consultancy
  • Temporary Resource Supply
  • Data Warehouse Design and Management
  • Operational Analysis
  • Predictive Analytics
  • Unstructured Data Analytics
  • Business Process Analysis and Consulting
  • Big Data Design and Management
  • Data Visualization and Dashboard Design
  • Statistical Model Design
  • Administrative Data Model Design
  • Performance Keys and Metric Analysis

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