Big data for big success

Almost all big worldwide known companies uses big data for improving their business and customers satisfaction, but do you know what that concept means?

The concept of big data can be explain with 5V:

– VOLUME – a huge amont of data

– VELOCITY – fast collecting of data,

– VARIETY – different types of data

– VERACITY  – accurate data

– VALUE – generates a new value

and it is a combination of data science, data mining, statistical and quantitative analysis, management skills, data visualization, programming, data structure and algorithms.

Therefore, big data is the same as data analysis, except that it is a large amount of data. That data can be structured, unstructured and semi-structured, based on the method of collection and storage.

Structured data is already stored in databases in an ordered manner. That are data from gps, medical devices, data of usage statistic captured by servers and aplications and the huge amount of data from trading platforms or it is generated by users (when user click on some link or make some move in a game).

Unstructured data are collected by humans (through social media, mobile data, website content – everything we watched or liked is unstructured data) and by machines (satelite images, the scientific data and radar data).

Semi – structured data are partially organized data, for example in NoSQL documents – which containts keywords that can be used to process the document easily

Data sources can be existing data, but there is an increasing need to use sensors on all devices, vehicles and products, as well as to create applications that can generate user data.

There are 4 types of big data analytisc:

  1. descriptive – explains what happend in the past based on data presented on graphics or reports but not predict what will happen in the future
  2. diagnostic – explains why something happend
  3. predictive  – predicts what could happen
  4. prescriptive – analyze, predicts and recommends  what to do

Infrastructure that is used for Big data consist of:

– storage systems and servers,

– data management and integration software,

– business intelligence and data analysis software and

– Big Data applications.

Technologies specific to Big data are

– Apache Hadoop – open source software for scalable, distributed computing,

– Apache Spark – an open source framework for cluster computing used to process Big Data within Hadoop,

– Data lakes – repositories that hold extremely large amounts of raw data in their original format,

– NoSQL data bases – store and manage data in a way that allows high speed and great flexibility,

– In-memory data base

Big data is not complex concept, but if you find a good idea, you can get many benefits from it. Find pattern in some behaviour or domain and use that knowledge. In next paragraphs you can read how some global companies uses big data:

– Starbacs generates data by more than 15 milion users (from customers ordering history) to find out type of coffee their users like and buy, in which time and place, and to send customized offers such as a birthday discount

– Netflix collects user behaviour data from more than 100 milion customers in order to learn what each of its customers likes and based on that  crates recomendation list for movies and series , which increase customer satisfaction

– Some game producers companies were analyzed in which parts of game users pause, restart or quit game and based on that data they have changed game story which improved user expirience

– Airbnb tracks customers preferences, based on key words from search and uses that data to generate offers

– Health industries uses big data for medical research, cost reduction and personilized treatment, predicting user response on treatment and terapies,

– In logistic sensors within vechiles are used to analyze the fastest route to reach the destination, based on information about the weather, traffic and orders,

– it can be used to track and allocate resources and reduce costs and for many other purposes.

Think about what you can do to improve your customer pleasure or what data you need to reduce costs or to improve profit. Learn more about customer and user behaviour, improve your products and services, find new ideas and create opportunities.