Self-Service Business Intelligence
Transform how knowledge workers
do their jobs
Move from Being Data-Rich to Data-Driven
Decisions must be made at the speed of business. For that, all people — from business users to data scientists and analysts — need to find trusted data quickly. Your data culture results when people are empowered to find the data they need and trust for smart decisions.
Building a Data-Driven Business
FIX THE DATA VALUE CHAIN
MAKE DATA EASIER TO DISCOVER
DISCOVER EXPERTISE AND COLLABORATE
BOOST ANALYST/SCIENTIST EFFICIENCY
ELIMINATE THE IT BOTTLENECK
REFOCUS ON CREATING
NEW DATA IP
Creating Effective Self-Service
Fix the Data Value Chain
Eliminate IT as a bottleneck to delivering data to business users, data scientists, and even business analysts. The request-based model does not provide data fast enough for today’s businesses — and this results in higher business costs, wastage, unresponsiveness to customers, and a lack of timely innovation.
Make Data Easier to Discover
Empower everyone to discover relevant data via an intuitive interface underpinned with deep connectivity to data sources — including data lakes, cloud data warehouses, and business intelligence tools. Allow users to find and understand data via natural language. Use faceted search to get relevant information faster. Convert technical terms to business terms and glossaries.
Quickly Determine Data Trustworthiness
Enable users to quickly determine data trustworthiness. They first access the catalog to discover their data, then assess data health with trust flags and user recommendations. Integrated data quality tools help ensure the right data is used appropriately.
Discover Expertise and Collaborate
Collaborate with other data users while discovering those with deep and rich expertise on data topics. This is critical for a growing remote/hybrid work population that needs to find and then connect with experts. Conversations and Wiki articles remove barriers to data collaboration, and enable broad community participation.
Eliminate the IT Bottleneck
“Prevent centralized IT and data engineers from obstructing the data needs of the larger population. Lower the volume of inquiry requests. Tap into existing knowledge so users don’t duplicate already-answered data queries. Users self-servicing data can directly determine whether their questions are answered. “
Refocus Analysts on Creating New Data IP
Companies have a limited number of analysts. Yet they are the linchpin to determining the speed at which data is provided to decision makers. It’s important for analysts to not recreate the wheel, but instead create new business insights. This is acheived when analysts can focus on evaluating new data sources as quickly as possible, with limited use of data engineering.
Increase Analyst and Data Scientist Efficiency
Once analysts and data scientists have discovered great data, they need to evaluate and leverage it. With Alation’s intelligent SQL editors, users can immediately query data — no matter where it resides. Inline suggestions guide people to the most relevant data, filters, joins, and queries. Wiki-like articles teach how to use the data accurately and compliantly.
What Is Self-Service in Business Intelligence?
Self-service is about enabling business users (and those supporting them) to get data when they need it, without an inquiry process. This reduces the decision-making cycle and results in a more agile organization.
How to Enable Self-Service Analytics and Business Intelligence?
Many things go into delivering self-service. Easier-to-use business intelligence tools help, but data discovery and contextualization is critical for more casual, non-power users involved with data and to drive a data culture.
Who Are the End Users of Self-Service BI Tools?
Self-service BI end users should be everyone in the company. The drive of self-service is to gain business agility by pushing decision making down in the organization — by having business users, analysts, and data scientists access data faster.
What’s the Difference Between Self-Service BI and Managed BI?
Managed BI is a model of business intelligence in which reports are built and distributed by report developers. Self-service is about enabling data users of all stripes to discover data and understand its trustworthiness.
What Does Self-Service BI Eliminate?
Self-service BI reduces data-inquiry volume. Users directly discover data and its trustworthiness. Analysts become more productive, focusing on new data sources and reports, which are easier to create as the volume reduces via efficient discovery.
What Does Self-Service Reporting Mean?
Self-service reporting allows business users to create reports and do ad hoc analysis. The population that needs data has grown, yet the number of power users has not. Thus, it's vital to make it easier for all business users to access data directly.
"The power of the data catalog is in the way it encourages people to interact with each other around our data, and contributes to people embracing this cultural and mindset shift. Now, people go to the data catalog and have an exchange when they have data or analytics needs."
Chief Data Officer, Parexel
"Users can search for and discover data, and ensure that data is properly governed and used in a compliant manner.”
Chief Data and Analytics Officer, Sainsbury’s
“[It's an] Amazon-like experience for data within Travelers. Now, non-technical users can look for and find the right data to meet their business needs."
Chief Data/Analytics Officer, Travelers
"Altogether, we now have more than 2,000 people using the platform inside the company. Within all the different parts of the company, there have been more than 250 use cases executed in a self-service mode by business users on the platform."
Head of Data Engineering, Munich Re
"We are moving from a culture of reporting to a culture of analysis. We are committed to helping everybody do a better job — from our adjusters to underwriters to agents. Our goal is to ensure relevant data is available to everybody."
VP of Info and Data Management, AmFam
"We are seeing a 99% time savings in finding the right data to write and execute queries: from 80 hours to 2 hours."
Director of Intelligence, Daimler