When you’re only relying on structured data for business analytics, you’re missing the big picture - this is where we can help you bridge traditional BI tools and practices with Big Data analytics and Splunk dashboards.
There is a unique opportunity to improve products, customer experience and business processes by expanding the scope of business analytics to incorporate data from new sources, such as machine data, web site logs, shopping cartS, applications, infrastructure components and database transactions.
Machine data hold a wealth of timely and relevant business insights that can provide a tremendous strategic advantage when made available for visualization, automation, alerting and reporting.
Splunk software analyzes, visualizes and monitors machine data from any source — such as applications, mobile devices and servers — to provide insights to IT and business operations on-premises and in the cloud. Delivering these enhanced business insights, in real-time, to your teams — including executives, sales, products, marketing, operations and customer service — can help transform your organization into a market leader.
Make use of advanced Big Data Analytics and visualization capabilities by:
- Leveraging a new class of data for business analytics and complement existing BI tools
- Gaining new business insights by enhancing machine data with structured data sources
- Analyzing machine data to identify patterns, outliers and trends to make better business decisions
- Detecting anomalies – incorporating Z-Score, IQR & histogram methodologies in a single command
- Using geospatial visualization – visualize metric variance across a customizable geographic area
- Displaying a single value – layering on visual cues for more business context and more flexible formatting
Business Process Analytics
Splunk let you gain real-time end-to-end insights into more complex business processes, such as trade settlements in banking institutions, order lifecycle management in retail and claim processing in healthcare. Slunk can optimize, for you, Keys stages in the process workflow by identifying bottlenecks. The Splunk platform can improve your customer experience with complete visibility into all transactions, and increase your revenue by gaining insight into why process steps failed often and let you fixing them promptly. It is comply with government mandates and regulations more easily.
Customer Experience Analytics
Splunk let you measure and analyze your customers’ behavior, and you can now understand their journeys across multiple channels to identify your new opportunities and then increase their engagement. Let’s uncover key insights on how your customers use and engage on your applications. Then from there, you will identify new ways to improve application response times and create business processes to meet customer needs, reduce drop-offs, raise site conversion, and increase revenue.
Understand and analyze production feature adoption, usage and effectiveness. Gain real-time insights into web and mobile product feature usage to gain deeper understanding of customer behavior. Identify user experience bottlenecks in real-time and pinpoint areas for improvement. Enable innovation, gain deep understanding of user engagement and user acquisition funnel, and increase product engagement.
Digital Marketing Analytics
Get real-time insights into marketing campaigns, user engagement and shopping cart conversion across multiple channels. Perform customer segmentation, measure marketing campaign effectiveness and track consumption and purchasing patterns. Increase conversion by optimizing the maketing funnel, improve SEO, enhance user engagement and improve marketing campaign effectiveness.
Splunk Analytics for Hadoop
Using Splunk Analytics for Hadoop, achieve unified queries and dashboards across unstructured data in Splunk Enterprise and Hadoop, which provide a single-pane-of-glass into real-time and historical data. Analyze and visualize months or years of data from a single, fluid user interface.
- Use 3rd-party Hadoop tools (e.g., Hive, Pig) to perform additional analysis
- Broaden data access to wider set of audiences, e.g. data scientists and analysts
- Run queries without moving or replicating data