Users Trends (Business analysts)

On the other side of the equation, power users require MAD capabilities 20 to 40% of the time. The bulk of their time is spent using tools designed to handle a variety of analytical tasks, including report authoring tools, spreadsheet-based modeling tools, sophisticated OLAP and visual design tools, and predictive modeling and data mining tools.

Times have never been better for power users. Their desktop computers contain more processing power and can hold more data than ever before. Today, there are more tools designed to help power users exploit these computing resources to analyze information. Many cost less than $1,000 for a single user or can be downloaded from the Internet. “Power users have more power today than ever to perform deep analytics,” .

Despite the plentiful options, many power users are bereft of optimal analytical tools. Either they restrict themselves to spreadsheets and desktop databases, or that’s all their organization will give them. Most homeowners wouldn’t hire a carpenter with just one or two tools in his toolbox; they want a carpenter whose toolbox contains tools for every type of carpentry task imaginable. In the same way, organizations need to empower power users with a multitude of tools and technologies to make them more productive as analysts. If implemented correctly, the technology can liberate analysts to gather, analyze, and present data quickly and efficiently without undermining enterprise IT standards governing data, semantics, and tools.

Four types. Power users are a diverse group who perform a variety of analytical tasks. I’ve divided power users into four types:

1. Business analysts. Data- and process-savvy business users who use data to identify trends, solve problems, and devise plans.

2. Super users. Technically savvy departmental business users who create ad hoc reports on behalf of their colleagues.

3. Analytical modelers. Business analysts who create statistical and data mining models that quantify relationships and can be used to predict future behavior or conditions.

4. IT report developers. IT developers, analysts, or administrators who create complex reports and train and support super users.

According to our survey, most organizations have all four types of power users, although only 51% have analytical modelers.

 

 

BUSINESS ANALYSTS. Business analysts sit at the intersection of data, process, and strategy, and they play a significant role in helping the business solve problems, devise plans, and exploit opportunities. Their titles include “business analyst,” “financial analyst,” “marketing specialist,” and “operations research analyst.” Executives view them as critical advisors who keep them grounded in reality (data) and help them bolster arguments for courses of action.

Business analysts perform three major tasks:
1. Gather data. Analysts explore the characteristics of various data sets, extract desired data, and transform the extracted data into a standard format for analysis.

2. Analyze data. Analysts examine data sets in an iterative fashion—essentially “playing with the data”—to identify trends or root causes. Analysts will visualize, aggregate, filter, sort, rank,
calculate, drill, pivot, model, and add or delete columns, among other things.

3. Present data. Analysts deliver the results of their analysis to others in a standard format, such as a report, presentation, spreadsheet, PDF document, or dashboard.

Today, business analysts spend an inordinate amount of time on steps 1 and 3 and not enough time on step 2, which is what they were hired to do. Unfortunately, due to the sorry state of data in most organizations, they have become human data warehouses. TDWI estimates that business analysts spend an average of two days every week gathering and formatting data instead of analyzing it, costing organizations an average of $780,000 a year.

According some survey, most business analysts use spreadsheets to access, analyze, and present data, followed by BI reporting and analysis tools. However, in most cases, the analysts use BI tools as glorified extract tools to grab data warehouse data and dump it into a spreadsheet or desktop database, where they normalize the data and then analyze it. The next most popular tool is SQL, which analysts use to access operational and other sources so they can dump the data into spreadsheets or desktop databases (which rank number five on the list, following OLAP tools).

 

 

To improve the productivity and effectiveness of business analysts, organizations should continue to expand the breadth and depth of their data warehouses, which will reduce the number of data sources that analysts need to access directly. They should also equip analysts with better analytical tools that operate the way they do. These types of tools include speed-of-thought analysis (i.e., subsecond responses to all actions) and better visualizations to spot outliers and trends more quickly.