Business Intelligence Job Roles – This knowledge is brought to you by business intelligence analyst and expert Megan Power, one of thousands of top business analytics consultants on .
The business world has never been more dependent on business intelligence capabilities. The rise in data analyst jobs in the US and the recent call in Australia to “teach kids coding in schools” suggest the future workforce will need to harness the magic of data and give them meaning.
Business Intelligence Job Roles
One of the challenges for business leaders, who will continue to need to leverage internal information to analyze performance, is the growing need to test as well; “What next?” scenarios “, ” and if ? and “what’s over there?” “.
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As global online commerce and consumer-driven markets for goods and services expand, relevant external information and trend analysis are essential to the continued competitiveness of businesses.
The challenge for all businesses is that disruption, including machine learning, artificial intelligence and big data analytics capabilities, is the new normal. Businesses can expect the need to access and apply intelligence over the next five years to continue to grow. Fortunately, new online tools and BI startups are filling the current gap in data analytics capabilities and capabilities.
This article aims to help the business manager understand the role of business intelligence analyst in order to enable his effective contribution within the organization.
If you are looking to establish a role for a Business Intelligence Analyst, this article also outlines some of the internal reasons why a BIA is appointed and the expectations regarding the breadth of skills that may be required to best meet the needs of the company.
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For those looking to contribute to a company in a business intelligence analyst role, this article will provide some insight into the role’s intersections in the business environment and the capabilities you can bring to the role.
As a key enabler, the aim of the role will be to support business competitiveness while identifying new opportunities for the business to move forward.
As any good intelligence analyst would do, I enlisted the help of fellow BI enthusiast Chris Ong, Head of BI and Development at Newcastle University, to prepare this article.
My experience covers qualitative intelligence and knowledge management with a background in geographic information systems and disease management systems in government. Chris describes his role as that of a problem solver: processes, data and people and has experience in industry and global business at BHP Billiton.
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We now share a common interest in intelligence management in higher education, both from the perspective of the education market and research development.
Business Intelligence (BI) can be described as the set of insights provided by data analysis and knowledge management, which can inform decision makers on areas of response. This may be related to emerging external trends or changing internal performance requirements.
A simple way to think about BI is to determine whether the data that informs business development goals comes from internal systems or external sources.
Internal information in large organizations will typically come from company-wide enterprise systems, such as SAP or ORACLE database systems, or may be drawn from a range of more comprehensive data capture systems. distributed and often informal within 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 relative to expectations. External sources may be directly focused on the business, such as market research that provides information on customer expectations or more formal analysis to identify “existing” trends that the business may need to respond to.
External information would also provide information on the competitive profile of similar companies. To respond to external changes, businesses can increasingly rely on external online “self-service” analytical resources.
In marketing, capturing social media trends through Google Analytics, Kissmetrics, or similar analysis tools is now a familiar activity, but making sense of all the information isn’t always straightforward. When describing the BI framework in an organization, Chris describes his perspective 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 challenged by web service options and less expensive and more agile cloud.
Senior Manager Mis Business Intelligence March 2024
In many large organizations, both forms of external and internal inquiry are merging through the Data Lake concept.
This takes over from formal data warehouse designs, where inputs are typically highly structured and outputs are aggregated for a standard level of reporting. Data Lake means that data can come from multiple sources and be “aggregated” into a less structured form that can be “mined” as needed with new analytical tools or scheduled queries.
Open source packages, such as Apache’s Hadoop, used by large online services such as Amazon, Twitter and eBay, are an example of a programming tool that can be deployed to extract data from a suite of clusters data storage.
This information is used to process data as well as to answer new business questions. Martin Fowler simply describes the Data Lake as a store for
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Data, regardless of the form provided by the data source. There are no assumptions about the data schema, each data source can use the schema of their choice. It is up to the consumers of this data to make sense of this data for their own purposes.
As shown in the chart below by Tamara Dull, Director of Emerging Technologies at SAS Best Practices, the growth of the Data Lake concept is also driving demand for data scientist skills to enable business intelligence analysts to stand out from other professionals .
While Martin suggests in his diagram that “we” select data for each need, the reality is that selecting, extracting and analyzing the “right” data from the Data Lake remains the domain of a data scientist or data scientist. a specialized analyst.
Table from Dull (2015) As the “single data system” prevalent in the enterprise suite of large organizations rapidly evolves toward more agile approaches, challenges remain around data security and statistical validity for Data Lake adopters. The structured data form will likely remain essential for some time for business-critical areas.
It Business Intelligence Analyst, Big River Communications, Cape Girardeau, Mo
Just as information management and information systems become less rigid, the Business Intelligence Analyst role requires a level of agility to inform and respond to the changing needs of the business.
The primary role of the Business Intelligence Analyst within an organization’s overall Business Intelligence system is to provide a vertical bridge across the enterprise to communicate high-value information to support decision-making demands. If the BIA role takes a “business knowledge” approach and the analyst is able to work with decision makers, information managers and external service providers to continually engage in business development, it is more likely to generate value. Often the first step in an inbound BIA is orientation and understanding the current state of the business.
BI must be able to take into account the organization’s existing systems as well as the company culture. They will need to understand “What are the business development objectives?” What data capture, storage and processing systems and mechanisms are applied? What methods are used for analysis, i.e. to what extent are the systems automated? How creative or mechanical are the requirements? »
The Business Intelligence Analyst may cover different parts of the organization, often working from a more internal or external perspective. In large organizations, BIA is expected to bring a level of insight into Big Data processing and could inform future intelligence collection priorities.
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As a first step, the BIA should work across the organization to take stock of the “4 Vs of Big Data,” a term coined by IBM to provide a framework that can inform business management. :
Although the types of skills required will depend heavily on the size and scale of the organization, the BIA can be expected to add value from the outset through technical, analytical and problem-solving skills. problems. They often have training and qualifications in information technology, data science and computer engineering.
Despite this background, the role should be clearly distinct from that of the IT or engineering specialist who may be expected to undertake analysis to build a business technology solution for the organization.
Rather than providing specific technical solutions, BIAs bring an understanding of data collection and analysis to the formation of intelligence and knowledge. In any organization this can be a broad activity that can cover:
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For corporate marketing-oriented BIA positions, an organization expects knowledge and experience across a wide range of social media platforms and media analytics tools.
For these positions, a double degree in information technology as well as communication and media would be an advantage. However, if the organization plans to expand this role in the future, or needs a BIA ready to move into a senior-level or management position, the job description will typically need to outline knowledge expectations broader commercial, communications expertise and potentially relevant sector experience. .
Successful candidates are generally expected to have postgraduate qualifications, such as
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