Digital transformation is a relatively new term. It refers to organizational change efforts that aim to:

• Improve an organization’s technology and tools
• Enhance employees’ digital skills
• Adopt new, modern business models

Today, the entire economy is digital. Businesses are regularly engaged in digital adoption, transformation, and change efforts .Because of this, the entire global economy is digitizing. Digital transformation helps businesses stay competitive in this environment. those that can transform effectively will survive, thrive, and succeed. Companies that are too slow to adapt
will lose their edge in the marketplace.

Digital transformation is affecting every industry, from retail to marketing to healthcare. The impact of digital transformation differs from industry to industry. The scale of that impact depends on factors such as:

• How reliant an industry is on technology
• What type of technology that industry uses – i.e., hardware or software
• The advancements of technology in general, and for that industry specifically

Regardless of the scale of that impact, every company is transforming to some degree.

A digital transformation project involves a number of steps, such as:

• The digital adoption of new technology, tools, software, and platforms, to maintain or gain a competitive advantage
• IT modernization, from infrastructure to hardware to software
• Implementation of digital-first business strategies
• Refocusing efforts on the customer experience

These disparate efforts follow global trends that prioritize customers and technology. Such trends contrast to “old-fashioned” business models that follow waterfall design approach.

Data mining is the process of digging through large amounts of data which allows businesses to discover patterns and predict future trends. Also known as ‘knowledge discovery in databases’,
data mining is normally applied under three disciplines:

• Statistics
• Artificial intelligence
• Machine learning algorithms

Advances in computing speeds has allowed businesses to automate this process so that they can step away from manual and time-consuming practices. Businesses such as banks, retailers, insurers and manufactures all use data mining to discover patterns in everything from pricing, economic forecasting, competition and social media, so that they can discover how they are affecting their business models, operations and client relationships.

Business intelligence is a term that covers the analytics, tools and processes which are used to optimize performance and make informed business decisions. Business intelligence is an umbrella term which covers:

• Data visualization
• Reporting
• Data mining
• Performance metrics
• Data preparation
• Statistical analysis
• Descriptive analytics

Business intelligence helps companies take an understanding of mass data so that it can be input into an intelligent enterprise model. This strategic approach allows teams and business leaders to identify useful information which would otherwise be lost in mass data.

Data integration is the process whereby you take data from different sources and combine it into one single source of truth. Data integration will often take place during the exploratory data analysis phase, where a researcher will include steps such cleansing, ETL mapping, combining data and transformation.
Data integration will often involve a few elements including a network of data sources, a master server and client data. During this process, the researcher will access the master server for data, extract that data and then consolidate it into a single cohesive data set.