With technology advancing like it is, more and more companies are finding the benefits and advantages of incorporating a business intelligence system in their program. For those not familiar, business intelligence consists of software and other tools that take complex business data and condense it into high-level reports. What can these reports be used for? A number of things. From increasing employee productivity to eliminating waste in the business place, business intelligence goes a lot further than just delivering reports.
Many executives now see business intelligence as a key buzzword. But what does this mean for the future of business intelligence? With business intelligence tools front and center in today’s marketplace, what will we see happen to this sort of popular business methodology as we move forward?
To answer these questions, we’ve made some predictions about the future of BI. The software is expected to become more collaborative, more proactive, more insightful and more equipped to handle Big Data.
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Collaborative Business Intelligence
One of the key business intelligence future trends many experts are predicting is a growth of the digital business intelligence world into a space where tools and platforms will become more broad-spectrum and eventually, more collaborative.
Many of today’s tools are siloed and independently operated by users — unconnected to a broader network. However, there is a consensus that the next generation
3. Ad Hoc Reporting
Ad hoc as a Latin phrase simply translates to “for this”. It refers to a solution that was created for a specific question or problem and is not meant to be changed or adapted for different tasks. Ad hoc reporting is a common business term that references a report or model that is produced for the purpose of answering a specific business question. The main reason for ad hoc reporting may be to fill in a blank on an as-needed basis where a regular report did not. Or, it may be used to aid the making of an important business decision. For example, as the manager of a shop, you may need to decide whether you should purchase new equipment. You can create some ad hoc reporting to determine if purchasing the equipment would increase profitability. Lastly, the data retrieved from an ad hoc report will
Will healthcare business intelligence (BI) be the answer that hospitals are looking for as they move to data-driven healthcare improvements and cost reductions? Yes … provided it’s built on the foundation of a data warehouse. Here’s why.
Healthcare is changing rapidly and so is the industry’s need for analytics and business intelligence, which brings up a problem: what exactly IS healthcare business intelligence? The term itself has multiple meanings and can be difficult to define, which leaves organizations that know they need a solution wondering exactly where to turn.
The trouble stems from the overuse of the term “business intelligence.” Sometimes business intelligence refers to a broad category of analytics, data warehousing and visualization tools, all of which are must-haves for any long-term and sustainable analytics foundation. Other times, business intelligence tools are linked to the visualization layer only – those tools that take the data and return
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Margaret Rouse asks:
What is your organization’s approach to the decision-making process?
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- Access an extensive library of delivered reports or create your own reports
- Display data in real time using rich, powerful visualizations
- Alert leaders of important metrics via automatic email notifications
- Understand why certain business trends are happening and respond appropriately
- Find opportunities for savings and improvements with various business intelligence
Today morning my co-worker asked me “What is Business Intelligence?” I looked at him, surprised. He surely knew what Business Intelligence meant. But he wanted a simpler answer from me. Something that is more specific, and easier to understand. I gave the Business Intelligence definition and explained Business Intelligence meaning in my own way, i.e. my take on the subject, from a Technical Communicator’s perspective.
Business Intelligence (BI) is the use of computing technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. Business Intelligence solutions provide current, historical, and predictive views of internally structured data for products and departments by establishing more effective decision-making and strategic operational insights.
Business Intelligence applications make use of online analytical processing (OLAP), reporting, predictive analytics, data/text mining, benchmarking, and Business Performance Management (BPM) to achieve accurate results.
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What is Business Intelligence?
Business intelligence is a data-driven process for analyzing and understanding how organizations work and make better decisions based on real insights. Business intelligence, or BI, has become a popular term across industries, but it is a catch-all term that encompasses various processes, tools, and methodologies that let companies capture data, analyze it, and derive better answers to key questions.
BI starts with the tools to capture data from across an organization’s operations so that every stakeholder can eventually access them. This includes the use of data warehouses and identifying them multiple data channels available to gain a deeper understanding of an organization. In an increasingly digital world, this translates into terabytes’ worth of data that must be properly contextualized.
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Another key aspect of business intelligence is the organization and analysis of these massive data sets to find unexpected connections, patterns,
Data warehouse – Test Data Mangement
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Test Data Management
Hope all are doing great….it’s very long time since I posted through my blog… my sincere apologies 😦
Test Data availability is the one of and most significant issue that will lead to Schedule slippage in DWH projects.
So the Testers and Test Managers should know what all are requirements for the test data and they need to define the test data strategy.
The Test Data Management should cover the below points:
- Subset of PROD data catered for Testing Requirements
Suppose if you are working in an Enhancement projects then you can avail the existing data that is already loaded into warehouse. In this instance you can’t use the data that’s pulled directly from Production as it’s sensitive to the Bank and its Customers.
- Mask the data