Business analytics
Confident decision-making demands modern data analytics
Introduction
What is business analytics?
Business analytics is a set of automated data analysis practices, tools and services that help you understand both what is happening in your business and why, to improve decision-making and help you plan for the future. The term “business analytics” is often used in association with business intelligence (BI) and big data analytics.
What are the benefits of business analytics solutions?
Make faster, more confident decisions
As data volumes increase, it’s nearly impossible to quickly and accurately process business data and spot hidden trends, patterns and business drivers. Modern planning analytics solutions can help customers experience 80% faster processing time.
Cut costs and increase velocity
Combine data across all sources to put insights into action faster, and automate your planning and analytics processes to save time and labor. Customers using planning analytics solutions have saved more than USD 1 million on streamlining their budgeting process.
Anticipate and respond to the unexpected
Predictive analytics let you forecast results and optimize outcomes. Test scenarios before implementing plans to see the potential impact of your decisions. Business analytics solutions give you the agility to alter plans and respond to changes with ease.
Which IBM solution is right for you?
Evolution
AI and the evolution of business analytics
The collection and analysis of data is fundamental to business analytics. In the 1990s, computer programming skills were needed to identify the available data in an organization, connect to myriad data sources, convert raw data it into a usable form, and generate periodic reports.
In the next decade, innovative companies began to analyze business data using programming languages like Python and R. This made it possible to see what was happening within their organization, and perhaps even why it was happening. But these practices left much to be desired for those who wanted to understand the true drivers of past performance, predict future events, and plan for the future—and they certainly weren't putting these capabilities in the hands of the average day-to-day worker.
Over the last decade, self-service business analytics programs, AI, and cloud data management software have made it possible for almost anyone (regardless of skill level) to analyze and visualize trends in real time, pinpoint business problems, and make informed business decisions. Business analysis is no longer limited to the domain of computer science professionals. It's a common tool for finance, manufacturing, healthcare, sales, marketing, supply chain, and operations, among others. If you are looking for insights from your data, you need business analytics.
Today, business analytics skills are taught at leading business schools and are an important part of many degree programs. Business students learn to apply their skills in real-world situations like business operations, where they identify key metrics and take a data-driven approach to problem solving.
Go beyond the what and get to the why and what’s next with business analytics solutions.
Business analytics lifecycle
The business analytics lifecycle helps organizations use data and information technology to identify what happened, why it happened and what to do next
Planning analytics
It starts with a plan. Whether it’s the corporate plan, financial plan, or one of many departmental plans, planning analytics provides insight into historical data to inform current plans and optimize for the future. Many businesses rely on excel spreadsheets for planning, but this process is time consuming and error prone. Modern solutions make it easy to create business plans collaboratively and responding quickly to actual business performance.
Descriptive analytics
Self-service business intelligence tools make it possible for everyone, from individual contributor to executive, to get a snapshot of business performance. However, it's critical to know that you can trust your data visualization tools and avoid acting on false insights. As the size of data sets increase, experienced analysts use automated tools to execute SQL queries, clean and combine multiple data sets. Data visualization is used to share trends and track KPIs.
Diagnostic analytics
Exploratory data analysis techniques make it easy to find relationships hiding in your data and identify real business drivers. Uncover what happened, and then determine exactly why it happened. AI-infused business intelligence solutions allow business users, business analysts and data analysts to easily apply data science algorithms, find unbiased insights at speed, and improve business decisions.
Predictive analytics
Self-service analytics tools have taken advantage of AI and machine learning to help business users and business analysts, not just data scientists, predict what will happen next by analyzing historical data and identifying patterns. Statistical analysis, python programming and data mining are just some of the advanced business analytics techniques used to predict outcomes.
Prescriptive analytics
Prescriptive analytics help you manage and allocate resources more efficiently and effectively by harnessing the power of optimization engines and statistical methods to sift through millions of possible alternatives and recommend the best decision. As you complete the business analytics lifecycle multiple times, you’ll begin to achieve new innovation driven by data.
Why IBM for business analytics?
Accelerate your analysis with AI
Automated Model Creation, Natural Language Processing, and Cognitive Help let you use data to inform faster and more confident decisions.
Our products are better together
Our analytics products are designed to work together as a broader set of business analytics solutions, and connect easily to your business information systems.
Deploy where and when you need it
Our products are available on premises, in the cloud, on IBM Cloud Pak® for Data or as a hybrid option.
I love empowering people to get the information, the data, the reports that they need.
Frances Fiorello, IT Manager, Reporting and Analytics, The University of Florida
We can use automated testing to quickly validate insights drawn from thousands of complex reports.
Zdenek Hanzal, Senior Analytics Architect, L’Oreal
We’ve been able to reduce our financial close process from 14-15 business days to four.
Jeffrey Qureshy, Financial Systems Senior Manager, Jabil
Resources
Learn more about topics related to business analytics
IBM Planning Analytics
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