Business Intelligence and Data Science | OpenTeQ

Business Intelligence and Data Science | OpenTeQ

OpenTeQ Admin | Updated: Jul 28,2020
Business Intelligence and Data Science | OpenTeQ

The term Business Intelligence (BI) refers to the methods for the presentation, collection, integration and analysis of business information.

The purpose of Business Intelligence is to help the companies in making better decisions. Business Intelligence helps usin many ways including briefing books, report and query tools and executive information systems.

In the current situation companies are in the middle of profound changes, during this times the amount of data available to the companies and rate of producing fresh data is growing rapidly. And as we know the business models and processimprovement methods rely on data and analytics.

Data science is a unique style or method through which knowledge is extracted from large structured or unstructured data sets. The method consists of data cleaning (preparing data for analysis), data analysis and data presentation (presenting findings) to inform high-level decisions in an organization.

We currently live in the time where there is access to artificial intelligence and smart applications and tools, also there is a rapid development happening in the sector of artificial intelligence.

There is a rapid growth in IoT (internet of things) and there has been an evolution for big data analytics which help businesses to make smart and wisely decisions and help them to get over their data and help them to achieve their objective. With the help of IoT growth there has been a growth of edge computing. In recent future Edge Computing will takeover mainstream cloud systems, it helps organizations to store streaming data close to the data sources so that they can be analysed in real-time.

Data services are online services which handles the programming logic for data virtualization in cloud data storage. Data services are useful when organizations needs to store data in more than one places and consumers of the data just need to find ways to analyse the data without bothering about the location of the data.

Data services gives companies more flexibilities on how and where to store data, also it gives companies a choice of location of storage of data with cost efficient, convenient to maintain location where the data is easy to find access.

Business Intelligence Services is a medium which a company uses to analyse its data and deliver the right information to the right people. Business Intelligence services use particular data science tools developed by them to analyse the data.

BI and data science have grown a lot since the past 2 years. 2020 has seen BI tools and strategies being more customised so far and the need for these tools will increase rapidly in coming years. We can say 2020 is a year of collaborative BI and Artificial Intelligence.

Some of the many trends seen in BI and data science are:

  • DQM (Data quality management): The principle of quality over quantity is described here. Loads of data from various sources are brought together and the useful data is stored together as a single data structure. The development of BI ensures that the data is clean and error-free. DQM consists of acquiring the data, implementing advanced data processes so as to put itin required format and then distributing the data effectively.
  • Data Discovery/Visualisation: The method oftaking out the maximum value from the metrics, insights, and information or data is called data discovery. The tools require for data discovery depends on the process and the generated findings become something of great business value. Using online data visualisation tools to perform these actions is becoming an invaluable resource in today’s world. Humans in the present level of development. Hence, the data discovery trend has chances of increasing to being one of the most important BI trends in 2020.
  • Artificial Intelligence: Artificial intelligence (AI) is the science aiming to make machines make decisions based on the training it received as what is usually done by complex human intelligence. Businesses are evolving from static reports of things happened in the past to dynamic analytics with live dashboards that help businesses to see what is happening at every second and give alerts when something is not how it should be. Another feature of AI in BI is the up scaled insights capability. This means that it fully analyses your dataset automatically without needing an effort from a person. Simply choosing the data source and the variable to be analysed and selecting the algorithm provokes the computation.
    That is an incredible time gain as what is usually handled by a data scientist will be performed by a tool.This provides business users with access to high-quality insights and a better understanding of their information, even without a strong IT background.
  • Data Driven Culture: A culture of depending on the statistical data will be enhanced. All decisions will be madekeeping in mind, the data pertaining to the history of the consequences of that decision. Implementing the data culture across departments can prove to be beneficial in many ways. The mentality of employees will change; data will be stored on the cloud where is easily accessible, accurate market segmentation will become a standard, and the costs will significantly decrease

In conclusion, now a days,organizations see data and content them under the same umbrella and started to manage them in an integrated manner instead of considering them as separate aspects of information management.

Operational Business Intelligence is booming in the current organizations and it is currently served and uncontested by vendors.

In early trends Business Intelligence vendors were targeting only the top of the pyramid but in the current trend there is a paradigm shift of Business Intelligence vendors to the bottom of the pyramid with an aim of self-service business intelligence.

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