Analytics
News, events, thought leadership and more.
With more types and warehouses of data, being a business or data analyst is more difficult than it ever has been. Transactional data and behavioral data is still as important as ever, but now it is critical to incorporate new types of data such as social media data to build, for example, a multi-channel marketing profile for a customer segment into your decision making process. And, while traditional data warehouses and data marts are often used to store the data, now there are big data systems such as Hadoop and MongoDB, and more and more data is being stored in the cloud. With all of these different options available, accessing and integrating the right data at the right time can be crucial to providing the right information at the right time, to the right person.
Most internal systems are typically managed or I should say guarded by IT or Data Warehousing teams. These teams are fantastic at managing your infrastructure and integrating your data. But many times, they can also be the roadblock to becoming a more agile organization—one that is able to react in minutes or hours (instead of days or months) to a data-related problem.
Becoming an agile organization starts with access to the right data at the right time. As I stated before most access to data is restricted to IT or a Data Warehousing team – and those teams can rarely keep up the contemporary business or data requirements the reality outline created.
This is where data blending can be utilized. What is data blending? Data blending is the process of combining data from multiple sources to create an analytic dataset used in business decision making. It can be used when the central management processes and infrastructure are unable to meet the deadlines required by the line of business groups. Analysts can use data blending when creating an analytic data set or where the specific dataset required for analytics cannot be easily brought together using that traditional data infrastructure. An example would be the rapid integration of customer information contained in a cloud sales automation system such as www.salesforce.com, click stream web data stored in an Apache Hadoop file system, and segmentation models stored in Microsoft Excel.
While organizations aspire to have a completely integrated data management system, the reality many organizations face is that a majority of the data required to make strategic business decisions exists outside that IT-controlled data environment. Alteryx Strategic Analytics gives line of business analysts and data scientists the ability to be agile. Alteryx delivers a unified platform giving access to all relevant data, the ability to blend that data, and produce analytics that can be consumed by decision makers anytime and anywhere.
To find out more visit our Analytics Gallery or download a 30-day trial.
Matthew Madden
Sr. Product Marketing Manager.
