Analytics

Overview

Businesses increasingly rely on data analytics to make sound decisions: to understand customers, optimize operations, and grow revenue. Analytics is only as good as the data behind it.

Which data to collect

The right data depends on your goals. Commonly analyzed types include:

• Customer data from surveys, social media, and support interactions
• Financial data from statements and accounting records
• Sales data from sales reports and invoices
• Marketing data from surveys, social platforms, and website data
• Web data from server logs, analytics tools, and public websites

Common techniques

• Data mining: extracting data from databases, websites, and social platforms to reveal patterns, trends, and relationships.
• Data cleansing: removing errors and inconsistencies so data is accurate and reliable.
• Data transformation: converting data between formats so systems can exchange it.
• Statistical analysis and machine learning: finding patterns and making predictions through classification, regression, and clustering.
• Natural language processing: extracting meaning from text, such as the sentiment of customer reviews.
• Data visualization: charts and graphs that make patterns easy to understand.

Benefits

Analytics identifies inefficiencies, guides resource allocation, reveals customer behavior and preferences, and uncovers new markets and product opportunities.

How epctex helps

We help analytics teams with data collection, cleansing, transformation, visualization, and mining, with a team of experienced data analysts ready to support your needs.