Demystifying Data Science VS. Business Intelligence VS. Big Data

DEMYSTIFYING DATA SCIENCE

DATA SCIENCE v/s

BUSINESS INTELLIGENCE v/s

BIG DATA

The world has been progressing at a supersonic pace. Businesses around the world are being guided by big numbers as they turn to digitization and virtual space. This has garnered a lot of attention from industry experts to make use of the vast data pool for futuristic business insights.

Mordor Intelligence Report suggests the Global Data Science Platform market to reach USD 133.70 billion by 2024 This is a clear indication of a plethora of Data Science roles and career opportunities on offer. With the US Bureau of Labor Statistics expecting a demand of 11.5 million for specialized Data Science professionals by 2026; worldwide organizations are going to benefit immensely.

It is not far that the entire business gamut is guided by the data game. Driving key business decisions is the way ahead. Data Science is levied with the heavy responsibility of becoming the driving force for the bigger game ahead. This is why it is essential to understand the core differentiators between Data Science, Business Intelligence, and Big Data. Let us take you through this in detail.

UNDERSTANDING DATA SCIENCE

Data Science encompasses Statistics, Data Mining, Data Modeling, Data Analytics, and Machine Learning to deduce and analyze data for drawing business insights. It is a diversified field of work that dwells upon the vast amount of data that is accumulated by the businesses in action. Business Understanding Data Understanding Data Preparation Modelling Evaluation Deployment

The Data Science workflow shown in the image above is a clear pathway that brings businesses closer to making beneficial decisions for the long run.

PERKS OF DATA SCIENCE

DRAWBACKS OF DATA SCIENCE

Users must possess expertise at Data visualization, Statistical analysis, and Machine learning

Time-consuming as regards Data preprocessing and cleaning

Ethical concerns while handling sensitive data

UNDERSTANDING BUSINESS INTELLIGENCE

Business Intelligence combines business analytics, data mining, data visualization, data tools, infrastructure, and best practices to assist organizations in making data-driven decisions. These are the set of strategies that guide the business actions in the future. The main purpose of Business Intelligence is to help inform and improve business decision-making by making data easier to interpret and act on.

DATA COLLECTION

DATA PROCESSING

Source: Medium

ACTIONS/ DECISIONS/ MEASURES

DATA ANALYSIS

DATA STORAGE

The Business Intelligence workflow represented above encompasses data collection, processing, storage, analysis, and actions that offer a string structure to a sturdy business model.

UNDERSTANDING BIG DATA

Big Data consists of a diverse variety of data that is collected over time with the increasing volumes and velocity of the data. In simple words, big data is larger, more complex data sets, especially from new data sources. Let us understand the 5 Vs of Big Data:

Terabytes, records, transactions, tables, files, etc

Batch, near time, real time, streams

Statistical, events, correlations, hypothetical

BIG DATA

Structured, unstructured, semi-structured

PERKS OF BIG DATA

Trustworthiness, authenticity, origin, reputation, accountability

Cost effective approach to efficient data management

Offers data for utilization and application of advanced analytics and machine learning

Processes complex unmanageable data by programming

Eases excess data interpretation for strategy building

DRAWBACKS OF BIG DATA

Only skilled professionals can handle associated tools

Security and privacy of sensitive data is ignored

Requires proper management and infrastructure

IS DATA SCIENCE AND BIG DATA THE SAME?

Not budget-friendly

Difficult integration with already in-use processes and systems

DATA SCIENCE

It is a field of work or domain

Collects, processes, analyses, and utilizes data for several operations

Generates data-based products for businesses

SAS, Scala, Python, R, others

Scientific purpose

IoT devices, system logs, public and company datasets, social media surveys

BIG DATA

It is a technique or strategy

Extracts data for interpretation

Converts data into a usable form

Spark, Hadoop, Apache, Flink, MongoDB, and more

Business purpose specifically for customer satisfaction

Social networking sites, weather forecasts, share markets, eCommerce sites, telecom companies

DATA SCIENCE AND BUSINESS INTELLIGENCE- SIMILAR OR DIFFERENT?

DATA SCIENCE

Extracts information from datasets and creates forecasts

Coding, data mining, advanced statistics, and domain expertise

Designed to manage large data sets

More complex in forecasting, and managing dynamic data, and requires advanced skills

BUSINESS INTELLIGENCE PARAMETERS

Identifying historical events and answering questions

Basic statistics and business knowledge

Designed to manage well-organized data

Less costly, requires fewer resources, practical for daily business management

DATA SCIENCE IN BUSINESS- THE OUTLOOK

Artificial Intelligence has spread its wings beyond industries, allowing enough expansion for every possible vertical to grow. With that, data science has managed to flourish in industries that are yielding big numbers as data sets that need to be deduced by skilled data scientists. Data Science is more research-based; it has a bigger role to play in enhanced business facilitation. Data-driven decision-making is the pivot that is guiding the big business moves today and tomorrow. With this exploration, businesses can reduce the risk of making poor choices and improve their overall performance.