A few weeks ago, we pointed out some new additions to Wolfram|Alpha from the World Bank’s World Development Indicators database, primarily focused on labor and employment around the world. We’ve also incorporated data about doing business in most countries, collected by a World Bank project called, appropriately, “Doing Business”.
This data covers a wide range of issues, including import/export costs, business tax rates, and the time required to complete various business-related activities. Try the following examples to get a better sense of the breadth of this dataset:
- Export costs in Brazil vs. Argentina »
- New businesses registered in Japan vs. India »
- Credit bureau coverage in Asia »
- Europe total business tax rate »
- How much does it cost to start a business in India, Mexico, Singapore »
- Time required to start a business »
Wolfram|Alpha can also rank countries according to a number of business-related indices. Ask about the ease of doing business in Eurozone countries, for example, and you’ll see that Ireland and Greece occupy the ends of this spectrum. In this case, a higher index score indicates a regulatory environment that is generally unfriendly to business operation; in light of Greece’s recent economic woes, it should come as no surprise to see that country at the bottom of the list. (Note that for all the properties in this dataset, you can click the “Definition” button in the input interpretation or in other pods to get more details on each property.)
Recently, CNNMoney published stories highlighting the “20 most profitable companies” and those considered to be the “20 biggest money losers”. Companies such as Exxon Mobil, AT&T, Apple, and Verizon were ranked by their 2010 profits, with each of the 20 profitable companies bringing in well over a billion dollars.
Using the information provided by both articles, there are many opportunities to gain more data on each of the companies from Wolfram|Alpha. For example, Exxon Mobil topped the list of most profitable companies, but has it always been profitable? Entering “Exxon earnings” into Wolfram|Alpha produces data and graphs documenting its earnings history.
Wolfram|Alpha recently added information about the minimum wage in U.S. states (from 1967 through today) based on data from the U.S. Department of Labor. This means you can ask Wolfram|Alpha about simple historical facts, like the U.S. minimum wage in 1980, or perform simple analyses, like comparing the current minimum wage in Ohio and Alaska.
A little over two months ago, we announced the addition of U.S. retail sales data to Wolfram|Alpha. With the holiday season upon us—and a great deal of attention focused on how current economic conditions will affect consumer spending this year—we thought it might be good to remind users of this functionality.
Retail sales data from the U.S. Department of Commerce always lags a few months behind the present, so the latest available data is for September 2010 (Wolfram|Alpha automatically picks up new data each month when it is released, usually around the 15th). But looking at sales categories that are highly seasonal, like jewelry stores, you can still observe some clear trends in the sales “spike” that occurs each December, with holiday-season sales way down in 2008, but recovering slightly last year:
Or choose “last 2 years” from the drop-down menu in the History pod to zoom in on the action a bit more and see how more recent trends match up against previous years:
You can also ask Wolfram|Alpha to analyze retail sales in a given category over any arbitrary date range for which data exists. Try asking about “U.S. clothing retail sales September 2005-September 2010” and you’ll get a result with the mean, maximum, and minimum value of retail sales over that time period—plus a zoomed-in view of retail sales in every category over those dates: More »
Wolfram|Alpha launched with an extensive database of United States economic data, derived from the Federal Reserve Bank’s FRED database. Over the past year, we’ve continued to improve our handling of this data in a variety of ways—teaching Wolfram|Alpha to return more related statistics along with any specific result, improving our linguistic abilities so we can answer more complex questions, and increasing the frequency with which we update this data. Wolfram|Alpha is now refreshing its collection of FRED-derived data on a daily basis, so you can always access the latest available data on the national economy.
We’ve also begun to expand our coverage of economic data for smaller geographic areas in the United States, starting with state-level statistics. This means Wolfram|Alpha users can now query for the latest available information on a variety of economic topics, including gross state product, unemployment, health insurance coverage, and housing-related data.
As always, one of the strengths of Wolfram|Alpha is that it allows you to compare and analyze different pieces of data—and with this data set, you can quickly uncover strong correlations between various economic properties. It’s easy to see that the house price index tends to move together with employment and state tax collections. You can also use Wolfram|Alpha to run simple calculations of productivity in U.S. states, or to find out a given state’s share of the national economy or workforce.
To make it even easier to explore this data, you can also use the new Wolfram|Alpha Widget Builder to create simple tools for analyzing and comparing the economic properties of states. To get you started, here’s a small selection of widgets focused on US state economies—ranging from the serious to the slightly silly. Try them out:
Hello, fellow readers of the Wolfram|Alpha Blog—my name’s Justin. In just a few short weeks, I’ll be graduating from the University of Illinois at Urbana-Champaign. Over the years I’ve found my own way of getting things done in regards to homework and studying routines. But this semester I realized there were tools available that would make studying and completing assignments easier and help me understand better. One tool that has become increasingly valuable in my routine and those of other students on my campus is Wolfram|Alpha. Recently, I was invited to share how Wolfram|Alpha is being used by students like myself.
Being a marketing major, I had to take some finance and accounting courses, but I was a bit rusty with the required formulas and the overall understanding of the cash flow concepts, such as future cash flows and the net present values of a future investment. A friend recommended I check out Wolfram|Alpha’s finance tools, and they’ve became indispensable in my group’s casework for the semester. Each proposed future investment we were met with, we would go directly to Wolfram|Alpha to compute the cash flows. We even went as far to show screenshots, such as the one below, of inputs and outputs in our final case presentation last week.
I’ve met other students on my campus who have found Wolfram|Alpha to be helpful in their courses. A few months ago while studying in the library, I walked by a table of freshman students all using Wolfram|Alpha on their laptops. I decided to stop and chat with them because I knew one of the girls. They explained how they were using Wolfram|Alpha to model functions and check portions of their math homework. All three girls are enrolled in Calculus III, and not exactly overjoyed about the fact of future— and most likely harder—math classes. More »
Prior to releasing Wolfram|Alpha into the world this past May, we launched the Wolfram|Alpha Blog. Since our welcome message on April 28, we’ve made 133 additional posts covering Wolfram|Alpha news, team member introductions, and “how-to’s” in a wide variety of areas, including finance, nutrition, chemistry, astronomy, math, travel, and even solving crossword puzzles.
As 2009 draws to a close we thought we’d reach into the archives to share with you some of this year’s most popular blog posts.
Rack ’n’ Roll
Take a peek at our system administration team hard at work on one of the
many pre-launch projects. Continue reading…
The Secret Behind the Computational Engine in Wolfram|Alpha
Although it’s tempting to think of Wolfram|Alpha as a place to look up facts, that’s only part of the story. The thing that truly sets Wolfram|Alpha apart is that it is able to do sophisticated computations for you, both pure computations involving numbers or formulas you enter, and computations applied automatically to data called up from its repositories.
Why does computation matter? Because computation is what turns generic information into specific answers. Continue reading…
Live, from Champaign!
Wolfram|Alpha just went live for the very first time, running all clusters.
This first run at testing Wolfram|Alpha in the real world is off to an auspicious start, although not surprisingly, we’re still working on some kinks, especially around logging.
While we’re still in the early stages of this long-term project, it is really gratifying to finally have the opportunity to invite you to participate in this project with us. Continue reading…
Wolfram|Alpha Q&A Webcast
Stephen Wolfram shared the latest news and updates about Wolfram|Alpha and answered several users’ questions in a live webcast yesterday.
We’re really catching the holiday spirit here at Wolfram|Alpha.
We recently announced our special holiday sale for the Wolfram|Alpha app. Now we are launching our first-ever Wolfram|Alpha “Holiday Tweet-a-Day” contest.
Here’s how it works.
From tomorrow, Tuesday, December 22, through Saturday, January 2, we’ll use Twitter to give away a gift a day. Be the first to retweet our “Holiday Tweet-a-Day” tweet and you get the prize! You can double your chances to win by following and playing along with Wolfram Research.
Start following us today so you don’t miss your chance to win with our Wolfram|Alpha “Holiday Tweet-a-Day” contest.
For active investors, the fast-paced nature of the trading floor requires having tools available to make confident decisions in a timely manner. Wolfram|Alpha offers a collection of money and finance tools ideal for finance professionals and personal finance matters. This data flows into Wolfram|Alpha in real time, providing traders with computation results in charts and graphs. In this post, we’ll look at a variety of ways Wolfram|Alpha can compute and present stock data.
Let’s start with the basics. Simply enter the name of a stock, such as Starbucks or its ticker symbol SBUX, into the computation bar. Wolfram|Alpha retrieves and analyzes both real-time and historical data, and presents the output in category pods. The pods display information such as the stock’s current value at last trade, its value at open and close, and range for that trading period. The “Fundamentals and financials” pod displays information such as the stock’s market share, revenue, number of employees, dividends, and more. Change the “Fundamentals” option on the right side of the pod to see additional information, including ratios, balance sheets, and income and cash flow statements.
We like to demonstrate ways Wolfram|Alpha can be a helpful tool for everyone. Today we’d like to share a cool feature Wolfram|Alpha users are talking about on the web. The Retirement Savior blog posted an item on Wolfram|Alpha describing how it can be used to calculate your retirement investments.
Wolfram|Alpha’s investment-returns calculator prompts you to describe your current investment strategy. Once you submit your query, Wolfram|Alpha will provide you with a number of results such as a linear chart depicting investment value projection scenarios, pie charts of resource allocation, a bar graph that allows you to easily compare the distribution of ages at which the account balance would reach zero, and a table displaying projections of your portfolio’s value at various ages. More »