Every business has receipts, invoices, customer letters, product descriptions, checks, and statements. In the internet age, companies still have all these things but multiplied and digitized.
An e-commerce titan like Amazon deals with mountains of data every day. Amazon began as an online bookseller and transformed into a ubiquitous marketplace, a cloud service provider, and a consumer device maker. Its business landscape is global, with many divisions and projects.
To make sound decisions, Amazon relies heavily on a specialized analytical process called business intelligence (BI). The company hires business analysts to use BI methods and tools throughout the entire company. BI analysts define ways to capture data. They analyze the results to gain insights into the organization, its products, and its customers.
The Business of Business Intelligence
BI means big data and generating business opportunities. Enterprises see the value in BI, and they invest accordingly. Good, consistent analysis helps a company understand its customers, tweak existing products, find issues, and can inspire new products and services. BI has found its place in the corporate world. It’s here to stay.
The initial phase of BI is the identification and capturing of data. Storing data is only the first requirement. Racks of servers act together to create a data warehouse.
Like farmers who winnow grains of wheat from the useless chaff, business analysts identify what data to keep and how to use it. Data channels are designed to funnel data for specific purposes. These channels are not based on business functions – a new product development channel can include a variety of data.
BI analysts can add customer search terms, suggestions, complaints about current products, third-party research, and vendor products.
Business Intelligence in the Marketplace
Business intelligence affects the independent merchants that use the Amazon marketplace. The question of why sell on Amazon needs business intelligence to provide the answer. Sellers access their dashboard reports on the Amazon Seller platform. They can study data about their inventory, product pricing, orders, payments, advertising, and general market performance.
Amazon’s continued investment in BI is reflected in updates to seller resources. The Seller Central Homepage has undergone a recent redesign. The page makes it easier for merchants to identify items requiring immediate attention like chargeback claims or shipping delays. Fifteen card tiles cover three data channels – merchant operations, account health, and seller resources.
The collection of data represented under the merchant operations section includes customer claims, chargebacks, and customer messages. These are sorted to display the most urgent items first.
The account health section reports any missing tax, rule violations, and seller account status. The seller resources tile has links to FAQs, updates, news, general support and help, and Amazon Pay integration testing.
Amazon has shown that BI can deliver benefits to all levels of their business, their customers, and merchants. Business intelligence gives Amazon merchants the ability to make better decisions, detect trends, resolve situations faster, and improve their individual business operations. Amazon Business Intelligence is set to continue driving efficiency and maintaining information value across all commercial units.
Jobs in Business Intelligence
The prominent players in the BI market include IBM, SAP, Oracle, and Adobe Systems. This is not surprising given the size of the BI market. They compete in a segment valued at $22.8 billion by Gartner.
By 2022, the market is expected to grow over $29 billion. These companies create sophisticated and powerful applications affecting databases, analytics, warehousing, and system administration.
Complex tools, rapid consumer technology advances, and heightened corporate expectations need a steady supply of qualified business intelligence analysts and engineers. The U.S. Bureau of Labor Statistics predicts growth of 21% for this job description up to 2024. Many industries are or will be employing BI professionals. These industries include finance, education, healthcare, and law enforcement.
Anyone interested in the BI field must possess an analytical mindset, business operations experience, and solid technical skills. In the early days of BI, employees with technical skills like programmers and system analysts were assigned to become data analysts. Nowadays, BI is a distinct specialty within IT and information management curricula.
The general education requirements and career path for a business intelligence analyst include:
- An undergraduate degree in computer science, business administration, information or data science, mathematics, physics, software engineering, economics, supply chain management or a related business field like organizational operations science.
- An internship is necessary to gain valuable work experience before graduation.
- Consider roles such as Amazon entry-level analyst jobs, general data analyst or report writer to gain experience and deeper business knowledge. These positions will hone skills in modeling, analyzing data, and working with commercial database systems.
- Take one step closer to a true business intelligence career with professional certification. The Microsoft Certified Solutions Expert certification in business intelligence covers SQL systems administration, data modeling, and data solution design. A period of work experience is necessary before attaining certification.
- Four to eight years of work experience is necessary before applying for BI analyst positions. Supervisory experience would be a plus.
- An advanced degree is desirable for further BI specialization. A master’s degree in information technology, business administration, or industry-specific discipline would be appropriate.
Through education and work experience, business analysts gain both business and technical skills. They use their business skills to understand different areas of a company and work with all staff levels.
Once the business needs are understood, technical skills are employed to design, build and operate databases, cloud architectures, reporting mechanisms, and data warehouses.
To progress to higher positions within a data-centric organization, a strong technical foundation is essential. A data analyst cannot settle on a limited set of skills. Over time they must cultivate a broad range of abilities.
An entry-level analyst should learn about and use Structured Query Language (SQL). They should have thorough knowledge about Relational Database Management Systems (RDMS). Computer languages should also be in the data toolkit. Finally, an analyst will use programming and scripting languages like Python, R, Perl, or Scala.
A company collects data from many sources. The data is rarely in an immediately useful format. It’s the analyst’s job to ensure incoming information is compatible with a company’s systems. Analysts need to be accomplished in data cleaning, validation, analysis, and visualization.
Once an analyst has proven their competence with data manipulation and querying, the next step is learning data warehousing and information architecture. They may begin by joining a team tasked with specific projects. These can include tasks related to data warehousing design, analysis, tuning, and ETL/ELT development. Information architecture exposes an analyst to the science of organizing and labeling all the raw data that a company owns or collects.
Beyond data competency, the next level is attaining knowledge in the actual hardware and services used for business intelligence operations. This can include certifications or workplace experience with cloud infrastructures like Microsoft Azure or Amazon AWS.
An analyst must know how everything fits and works together. Senior positions involve IT platform implementation, migration, troubleshooting, and maintenance.
Once an analyst has reached the level of working on data warehousing tasks, another career path is possible. Analytics focuses on interpreting existing data and generating reports to aid in strategic decision making. Data analysts work to improve data quality and infrastructure.
Business intelligence scientists ask questions, look for patterns, and create algorithmic statistical models. They develop new tools and methods of automation on their own. This discipline requires a higher level of programming knowledge than an analyst role.
A scientist works to predict what new products, services, or trends are likely to be and their impact on the company.
Data scientists are as equally in demand as analysts.
Business intelligence is a demanding, competitive field with a bright outlook and attractive pay packages. An Amazon entry-level analyst salary starts at $36,000 and increases with experience, technical certifications, and advanced degrees.
The most experienced analysts and data scientists can make well over $100,000. Analyst jobs are not confined to big cities like Chicago. Positions are available throughout the country from San Jose to Nashville.
It is possible to transition to business intelligence from other IT positions. A programmer can learn data specific skills. By learning data applications and programming languages, a systems analyst can shift to BI.
Business Intelligence Evolution
Business intelligence applications help companies make sense of an endless stream of information. Data analysts use their knowledge and expertise to find problem areas, suggest solutions, and predict future trends. They recommend strategies for growth, improvement, efficiency, and stability in uncertain times. Large enterprises rely on business intelligence methods and insights every single day.
As analysts learn more about a business, their value will rise. Experienced business intelligence analysts have the flexibility to assume roles that are best aligned with the business side rather than the technical side. They can be marketing analytics managers, project managers for corporate IT applications, or customer-facing BI architects working as in-house consultants.
BI knowledge of enterprise applications is valued across many industries. A data analyst or scientist in the e-commerce field can specialize in Oracle or SAP BI applications and tools. Their knowledge will remain useful in unrelated industries such as construction or insurance.
A career in business intelligence analytics needs perseverance and constant learning. However, it is a career that has worldwide demand and numerous options for change and advancement.