Business Intelegence Analyst

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The business world has never been more reliant on business intelligence capabilities. The increasing hiring of data analysts in the US and the recent call to ‘teach kids coding in schools’ in Australia indicate an understanding that the workforce of the future will need to harness the magic of data. and make it meaningful

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Challenges for business leaders who need to use internal data for performance analysis So is the increasing demand for testing. ‘What next?’, ‘What if?’ and ‘What if?’ scenarios.

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As the global online business and consumer-led goods and services market grows, Relevant external data and trend analysis are therefore vital to continued business competition.

The challenge for every business is that disruption is the new norm with machine learning. artificial intelligence and the ability to analyze big data, businesses can expect to access and apply intelligence over the next five years to continue expanding their businesses. Fortunately, new online tools and expert BI startups are bridging the current capabilities and capability gaps in data analysis.

This article aims to support business managers’ understanding of the role of business intelligence analysts so that they can effectively feed data into their organizations.

If you are considering establishing a Business Intelligence Analyst role This article explains some of the internal reasons for hiring a BIA and expectations regarding the diverse skills needed to meet business needs.

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For those wanting to support the business in a Business Intelligence Analyst role. This article provides insights into where roles intersect in the business environment. And what skills can you bring to that role?

As an important factor This role will aim to support the competitiveness of the business. and identify new opportunities To drive the business forward

Like any good intelligence analyst, I called Chris Ong, BI and Development Manager at Newcastle University, a BI enthusiast, to prepare this article.

My experience includes qualitative intelligence and knowledge management with a background in geographic information systems and disease management systems in the public sector. Chris describes his role as a process, data and people problem solver and has experience. in global industry and business with BHP Billiton

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We currently have a shared interest in intelligence management in higher education from both an education market and a research development perspective.

Business intelligence (BI) can be described as a set of data generated by data analysis and knowledge management. This can inform decision makers about areas of response. This may be related to emerging external trends or changes in internal performance requirements.

A simple way to think about BI is to look at whether the data that informs business development goals is pulled from internal systems or external sources .

Internal data in large organizations often comes from enterprise systems across the business, such as SAP or ORACLE database systems, or can be drawn from more distributed and often informal data collection systems across the organization.

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This data can then be analyzed for BAU reporting and tested against other data. To determine how the organization is performing against expectations. External data sources may be based directly on the business, such as market surveys that provide information on customer expectations. or more formal analysis to identify trends that the business may need to respond to.

External data also provides information about the competitive position of the business in response to external changes. Businesses may also use online analytics resources. ‘Self-service’ from outside is increasing

In marketing Tracking social media trends through Google Analytics, Kissmetrics, or similar analytics tools is a familiar activity. But understanding the range of data isn’t always straightforward. When explaining the BI framework in an organization, Chris explains his approach with an analogy to an onion.

Like any element of a business, end-to-end business intelligence must deliver value. And the cost of deploying and deploying large enterprise information systems is being challenged by more agile, low-cost web and cloud-based service options.

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In many large organizations Both types of data intelligence needs, both external and internal, are combined through the Data Lake concept.

This is taking over from the formal data warehouse design. Where inputs are typically highly structured and outputs are packaged to a standard reporting level, a data lake means that data can come from multiple sources and be ‘aggregated’ into a less structured format that can be ‘taped’ accordingly. required with new analysis tools or programmed queries

Open source packages such as Apache’s Hadoop, which is used by major online services such as Amazon, Twitter, and eBay, are examples of programming tools that can be used to extract data from a set of storage clusters.

This information is used to process data as well as answer new business questions. Martin Fowler simply describes a data lake as a store.

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Information, resources are provided in any form. There are no assumptions about the data schema. Each data source can use whatever schema it wants. It is up to the consumer of that information to interpret that information for their own purposes.

As shown in the table developed by Tamara Dull, Director of Emerging Technologies, SAS Best Practices, the growth of the Data Lake concept is also increasing the demand for data scientist skills to empower Business Intelligence Analysts more than any other business professional.

Martin suggests in his diagram that ‘we’ select data for each need. But the truth is that selecting, extracting and analyzing the ‘right’ data from a data lake is still the domain of the data scientist or expert analyst .

Table from Dull (2015) Although the ‘one size fits all information systems’ prevalent in the enterprise suite of large enterprises are rapidly shifting towards a more agile approach. Challenges regarding data security and statistical accuracy continue to exist for data lake users. Structured data forms have remained essential for business-critical sectors for some time.

Business Intelligence Analyst Dashboard On Virtual Screen. Big Data Graphs Charts Stock Photo

This is because data management and information systems are less stringent. The role of a business intelligence analyst requires agility to inform and respond to changing business needs.

The primary role of a business intelligence analyst in an organization’s overall business intelligence ecosystem is to provide a vertical bridge through the business to communicate high value information to support decision-making needs. If the BIA’s role is to take a ‘business insights’ approach, and be able to work with analyst decision makers. data manager and external service providers to participate in continuous business development The more likely you are to deliver value, the first step in a BIA is to understand the current direction and state of your business.

BI needs to be able to consider an organization’s existing systems as well as the culture of the business. They must understand that ‘What is the objective of business development? What systems and mechanisms are used for data collection, storage and processing? What methods of analysis are used, for example, how automated is the system? How creative or mechanical are the requirements?”

Business intelligence analysts can span different parts of an organization, often working from a more internal or external perspective. In large organizations, BIAs are expected to bring a level of knowledge about big data management. and inform future intelligence collection priorities.

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As a first step, BIA is expected to work across the organization to align inventory around the “4 ‘V’s of Big Data,” a term coined by IBM to create a framework that can inform business management. can:

While the type of skills required is highly dependent on the size and scope of the organization, BIAs can expect to add value from the outset through technical, analytical and problem-solving skills. They usually have a background and qualifications in information technology. data science and computer engineering

Even with this basic But that role must be clearly different from an IT or engineering professional who might be expected to perform analysis to create business technology solutions for an organization.

Rather than providing a specific technical solution, BIA leverages data collection and analysis to inform intelligence and knowledge generation. In any organization, this can be a broad spectrum of activities. That may include:

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For a BIA role focused on business marketing Organizations expect knowledge and experience in a variety of social media platforms and media analytics tools.

A dual degree in Information Technology as well as communications and media qualifications can be beneficial for these roles, however, if the organization expects the role to expand in the future. or need to create a BIA to advance to a senior or executive level position. The job description must typically explain the expectation for extensive business knowledge. communication skills and experience In fields that may be related –

Successful applicants will normally have postgraduate qualifications such as:

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