Data Technology

Data technology sector includes solutions for data management, and products or services that are based on data generated by both human and machines. Data Technology is an emerging industry that uses Artificial Intelligence, Big Data analysis and Machine Learning algorithms to improve business activities in various sectors, such as digital marketing or business analysis (e.g. predictive analytics).

 

Data technology has been used to manage big data sets, build solutions for data management and integrate data from various sources to discover new business or analytical insights from collected information.

 

Data technologies are developed to help manage data generated by human or by machines. Data technologies aim to manage growing data streams, get valuable insights from data and find solutions to integrate the most important data sources for companies and organizations.

 

Therefore, key areas for Data Technology sector are:

1. Data Management Technologies - technologies and platforms for managing growing sets of data, such as data generated by customers. Common platforms for managing data are Data Management Platform or Customer Data Platform.

 

2. Data Integration - services that match the data from two or more sources to get more information about stored data. If company collects user data in Customer-relationship management system, it can enrich it with the data from external sources to create 360⁰ - customer view (by integrating data, the company will know e.g. interests, demography and intentions of users who are in their databases).

 

3. Data Consulting - services based on analysing customer data and discovering insights from big data sets. It uses Machine Learning algorithms to find useful information from chaotic data.

 

4. Technologies for Advertising Technology sector - products and services that support digital marketing environment, Demand-side platform and services used for targeting the right group in online campaigns.

 

5. Building strategic data ecosystem - service that allow to build data ecosystem in organization, by identifying and choosing the right data sources, integrating data and preparing adequate analytical algorithms to discover new insights about customers.

 

6. Internet of Things - products and services that helps store and manage data generated by machines.

 

BIG TECHNOLOGY

Big data is a specific indicator for the vast assembly of data, increasing enormously in size and exponentially with time. Big Data Technologies can be defined as software tools for analysing, processing, and extracting data from an extremely complex and large data set with which traditional management tools can never deal.

 

Big Data Technologies are broadly classified into two categories.

 

1. Operational Big Data Technologies

Operational Big Data Technologies indicates the volume of data generated every day, such as online transactions, social media or any information from a particular company used for analysis by software based on big data technology. It acts as raw data to supply big data analysis technology.

Few cases of Operational Big Data Technologies include information on MNC management, Amazon, Flipkart, Walmart, online ticketing for movies, flights, railways and more.

 

2. Analytical Big Data Technologies

Analytical Big Data Technologies concerns the advanced adjustment of Big Data Technologies, which is rather complicated than Operational Big Data. This category includes the real analysis of Big Data, which is essential to business decisions.

Some examples in this area include stock marketing, weather forecasting, time series and medical records analysis.

 

TOP 5 BIG DATA TECHNOLOGIES

1. Hadoop Ecosystem

Hadoop Framework was developed to store and process data with a simple programming model in a distributed data processing environment.

 

2. Artificial Intelligence

Artificial Intelligence is a broad bandwidth of computer technology that deals with the development of intelligent machines capable of carrying out different tasks typically requiring human intelligence.

 

3. NoSQL Database

NoSQL includes a wide variety of different Big Data Technologies in the database, which are developed to design modern applications. They are used in Web and Big Data Analytics in real-time. Facebook, Google, Twitter, and similar companies store user data terabytes daily.

 

4. R Programming

R is one of the open-source Big Data Technologies and programming languages. Ths software is widely used for statistical computing, visualization, unified development environments such as Eclipse and Visual Studio assistance communication.

 

5. Data Lakes

Data Lakes means a consolidated repository for storage of all data formats at all levels in terms of structural and unstructured data.

 

This Big Data technology helps enterprises respond to better business growth opportunities by understanding and engaging clients, sustaining productivity, active device maintenance, and familiar decision-making to better business growth opportunities.

 

THE FUTURE HOLDS FOR BIG DATA TECHNOLOGIES

The Big Data environment is continually evolving. Very easily, the latest innovations in Big Data Technologies are being launched, many of which will increase based on the demand in the IT industry. These innovations will ensure that there is harmonious functioning for the development of businesses.

 

Big Data is still very much rising with more adoptions and more applications of the existing Big Data technologies and the launch of newer solutions related to Big Data security, Cloud integrations, data mining etc.