Business Intelligence Developer Return To Goal – This knowledge is brought to you by business intelligence analyst and expert Megan Power, just one of the thousands of leading business intelligence consultants on .
The business world has never been more dependent on business intelligence. The increase in data analyst employment in the US and the recent call in Australia to “teach coding to kids in schools”, suggest an understanding that the future workforce will need to capture the magic of data and make it meaningful.
Business Intelligence Developer Return To Goal
One challenge for business leaders who will continue to need to leverage internal information for performance analysis is the growing need to also test; ‘what next?’, ‘what if?’ and ‘what’s out there?’ scenarios.
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As global online commerce and consumer-led markets in goods and services grow, relevant external information and trend analysis are key to continued business competitiveness.
The challenge for all businesses is that disruption, including machine learning, artificial intelligence and Big Data analytics capabilities, is the new norm. Businesses can expect the need to access and apply intelligence in the next five years to continue to expand. Fortunately, new online tools and specialized BI startups are filling the current capacity and capability gap in data analytics.
This article aims to support the business manager’s understanding of the role of a business intelligence analyst to enable their effective input within the organization.
If you are looking to establish a role for a business intelligence analyst, this article also describes some of the internal reasons for appointing a BIA and the expectations for the range of skills that may be required to best address the business need.
Bs In Business Intelligence And Data Analytics
For those looking to contribute to a business as a business intelligence analyst, this article will provide some insight into where the role intersects in the business environment and what skills you can bring to the role.
As a key enabler, the aim of the role will be to support business competitiveness by identifying new opportunities for the business to move forward.
As any good Intelligence Analyst would do, I called on fellow BI enthusiast Chris Ong, BI and Development Manager with the University of Newcastle to prepare this article.
My experience covers quality intelligence and knowledge management with a background in geographic information systems and disease management systems in government. Chris describes his role as a problem solver: process, data and people and he has experience in the industry and global business with BHP Billiton.
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We now have a common interest in intelligence management in Higher Education from both the education market and the research development perspectives.
Business Intelligence (BI) can be described as the sets of information made available through data analysis and knowledge management that can inform decision makers about areas for response. This may be in relation to emerging external trends or changing internal performance requirements.
A simple way to consider BI is to look at whether the data that informs business development goals is drawn from internal systems or external sources.
Internal information in large organizations will generally come from business wide enterprise systems, such as SAP or ORACLE database systems, or may be drawn from a variety of more distributed, and often informal, data capture systems from across the organization.
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This data can then be analyzed for BAU reporting and tested against other information to identify how the organization is performing against expectations. External sources can be directly driven by business, such as market surveys that provide information about customer expectations or more formal analysis to identify what trends are “out there” that the business may need to respond to.
The external information would also provide information about the competitive profile of similar businesses. In responding to external change, businesses may increasingly use external “self-service” web analytics resources.
In marketing, the capture of social media trends using Google Analytics, Kissmetrics or similar analysis tools is now a familiar activity, but understanding the set of information may not always be straightforward. When describing the BI framework in an organization, Chris describes his view with the onion analogy.
As with any component of a business, the broader Business Intelligence System must deliver value and the cost of adopting and adapting large enterprise data systems is being challenged by lower cost and more agile cloud-based and web services.
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In many large organizations, the two forms of external and internal information intelligence demand are merged through the Data Lake concept.
This takes over from formal Data Warehouse designs, where inputs are typically highly structured and outputs are packaged for a level of standard reporting. The Data Lake means that data can come from multiple sources and be “aggregated” in a less structured form that can be “tapped” as needed with new analytical tools or programmed queries.
Open source packages, such as Apache’s Hadoop, which is used by large Internet services such as Amazon, Twitter and eBay, are an example of a software tool that can be deployed to pull data from a set of data storage clusters.
This information is used to process data and address new business inquiries. Martin Fowler simply describes the Data Lake as a store for
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Data, in whatever form the data source provides. There are no assumptions about the schema of the data, any data source can use whatever schema it likes. It is up to the consumers of that data to make sense of that data for their own purposes.
As shown in the table developed by Tamara Dull Director of Emerging Technologies, SAS Best Practices below, the growth of the Data Lake concept is also driving the demand for data science skills to enable business intelligence analysts over other business professionals.
While Martin suggests in his diagram that “we” select data for every need, the reality is that selecting, extracting and analyzing the “right” data from the Data Lake is still the realm of a specialist data scientist or analyst.
Table sourced from Dull (2015) While the “one-size-fits-all data system” prevalent in the enterprise suite of large organizations is rapidly changing to more agile approaches, challenges remain around data security and statistical validity for the Data Lake adopters. The structured data form is still likely to hold as essential for some time to focus business critical areas.
Business Intelligence: A Complete Overview
Just as information management and information systems are becoming less rigid, the role of a Business Intelligence Analyst requires a level of skill to inform and respond to changing business needs.
The principle role of the Business Intelligence Analyst within an organization’s overall Business Intelligence System is to provide a vertical bridge across the business to communicate information of high value to support decision-making requirements. If the BIA’s role takes a “business insights” approach and the analyst is enabled to work with decision makers, information managers and external service providers to continuously engage in business development, they are more likely to deliver value. Often the first step for an incoming BIA is orientation and understanding of the business’s current state.
The BI must be able to consider the existing systems of the organization as well as the culture of the business. They will need to understand ‘What are the business development goals? What systems and mechanisms for capturing, storing and processing data are applied? What methods are used for analysis, so how automated are the systems? How creative or mechanical are the requirements?’”
The Business Intelligence Analyst can span different parts of the organization, often working from either a more internal or external point of view. In large organizations, the BIA would be expected to bring a level of knowledge of Big Data handling and could be expected to inform future intelligence collection priorities.
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As a first step, the BIA can be expected to work across the organization to provide a stock position around the “4 ‘V’s of Big Data”, an expression coined by IBM to provide a framework that can inform business management:
While the types of skills required will be highly dependent on the size and scale of the organization, the BIA can be expected to add value from the start through their technical, analytical and problem solving skills. They will often come with backgrounds and qualifications in Information Technology, Data Science and Computer Engineering.
Despite these backgrounds, the role must be clearly distinct from the IT or Engineering specialist who may be expected to perform analysis to build a business technology solution for the organization.
Rather than delivering specific technical solutions, BIAs bring an understanding of data collection and analysis to intelligence and knowledge formation. In any organization this can be a broad activity that can cover:
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For business marketing oriented BIA roles, an organization would expect knowledge and experience across a wide range of social media platforms and media analytics tools.
For these roles a double degree in information technology as well as communications and media qualifications would be an advantage. However, if the organization anticipates expanding the role in the future, or needs a BIA ready to step into a senior or management-level role, the job description will usually need to describe expectations for broader business knowledge, communication expertise and potentially relevant sector experience. .
Successful applicants would normally expect postgraduate qualifications, such as
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