We are loving this article by Neil Raden on diginomica.com, I’m Feeling Sentimental about OLAP and You Should Too. In it Raden makes the case that the OLAP tech that existed in the 90’s plus the new strides that have been made in recent years as far as scale, speed, CPU power, and functionality, makes OLAP a very strong contender in the business solutions space.
In his article, Raden writes, “OLAP gave people the ability to interact visually with the data and explore it using the multidimensional models of attributes, metrics, filters, and calculations, at minimum. Without code.” This is still an amazing value proposition! He admits, “OLAP had lots of drawbacks, but many of them have been resolved by the advance of computing resources. A mid 90’s OLAP implementation may have been running in 1/100,000th the resources routinely available now.”
Raden takes the reader through some important basics about OLAP tech, and it is definitely worth reading through his succinct explanations. One that really resonated with us at OLAP.com is this about the need for OLAP: “All of the data science in the world can’t match the capability of OLAP to explain the status of an organization, because at the end of the day, someone still has to count the beans.” And we know this to be true. And we are all about smarter, faster, better ways to count those beans and make better business decisions.
Find Neil Raden’s original article here on diginomica.com
Check out this cool infographic! Submitted to OLAP.com by the folks at Business Intelligence Technologies. They’ve mapped here 5 warning signs that you and your professional team are living in Excel Hell. Perhaps it’s just been accepted that your Excel Hell is what it is, but we beg to differ. Professional teams overuse Excel, to a point way beyond what it was designed to do as a personal productivity tool. This fact has led to many technology and BI software vendors positioning themselves against Excel as if it is something to be removed. Sacrilege, cry the users! And us too! People responsible for planning in particular, need the flexibility that Excel provides and find almost any other tool too rigid. (See the Wall Street Journal article: Finance Pros Say You’ll Have to Pry Excel Out of Their Cold, Dead Hands) So, if Excel is essential, how do we get free from Excel Hell?
For further reading, see the blog on this topic on the Business Intelligence Technologies website.
7 Key Business Intelligence Software Trends for 2019
By Keith Craig, Better Buys
Peter Drucker, father of the Knowledge Economy and business management guru said, “Knowledge has to be improved, challenged and increased constantly, or it vanishes.”
Nowadays, vanishing isn’t the worry. Rather, that knowledge – in the form of raw data – has been constantly and exponentially increasing. Data sources are myriad and everywhere.
Have a doctor’s appointment? Your vitals, diagnosis, and Rx get databased. Engage an e-commerce website? Your keystrokes and submitted information get funneled to a CRM. Run a factory? Smart machines record their performance metrics. Involved in a supply chain? Data on product distribution and raw material use gets monitored and stored for future reference.
With this ever-increasing aggregation of factual data, software platforms – many utilizing Online Analytical Processing (OLAP) technology – facilitate ad-hoc analysis across multiple dimensions. Once the data has been stored, BI software slices, dices, and juliennes it. Visualizations yield insight through charts and graphs that populate dashboards. Such business intelligence software delivers value by generating real-time analytics that delineate trends, from which company principals can confidently make proactive decisions rooted in facts.
The impact to your business? Decisions rendered from Business Intelligence improve personnel, product and user experiences. Your company runs better. Staff is content and productive. Customers are happy. Product moves. Revenue climbs. Profits soar.
Drucker would be thrilled with today’s Business Intelligence software, which by its very nature improves and challenges marketplace and workplace knowledge. He would find it unsurprising that the trend to use Business Intelligence software continues to surge.
The following infographic on 7 Key Trends reflects this sustained momentum, popularity, and utility of Business Intelligence software as we move toward 2019.
Keith Craig is Content Marketing Manager for Better Buys. He has more than a decade of experience using, researching and writing about business software and hardware. He can be found on Twitter and LinkedIn.
Not too long ago businesses found it very difficult to query data out of their recently acquired relational databases. These queries were too slow to be processed by computer systems of the time as well as too inflexible to navigate the data. After trying different solutions offered by various big corporations in the market, OLAP came into being.
One of the primary goals that OLAP vendors try to achieve is to minimize the amount of on the fly processing needed when the user was simultaneously navigating the data. This was achieved by pre-processing and storing every possible combination of dimensions, measures, and hierarchies before the user started their analysis.
The earlier versions of the OLAP cube provided a snapshot of data at a specific point in time. OLAP pre-computes all the totals and sub-totals that need to be reported at a time the servers are usually idle. This allowed data to appear at the same time as it was being investigated by the user.
Because OLAP cubes pre-calculate all the resulting combinations between dimensions, you can do some amazing analysis. For instance, all at once, you can analyze sales by region, by product type, by period of time, by store, by sales representative, and by budget. Crazy, right? It gets so overwhelming that sometimes you may have to back up and try to figure out what kind of analysis you are trying to do. With practice, OLAP cubes speeds up the data modelling and analysis process by significantly minimizing manual operations.
Here are some interesting facts about the history of OLAP technology:
- Edgar Codd, the person who designed the OLAP cube and coined the term OLAP (Online Analytical Processing), he is a veteran in the field.
- SEQUEL (Structured English Query Language) was actually the first version of SQL (Structured Query Language).
- ‘Slice’ among OLAP technicians means dividing any cube shaped item into two.
- The OLAP cube is made up of dimensions, measures, and hierarchies.
- Arrangement of data into a cube is what allows large amounts of data to be analyzed as it is displayed instantaneously.
- The query language used to interact and perform tasks using an OLAP cube is called multidimensional expressions (MDX). It was first developed by Microsoft in 1990s and then got taken up by numerous other vendors in the market.
- OLAP cubes are designed for business users and therefore use business logic and understanding. However, business users can query OLAP cubes using Standard English.
Since its early beginning, OLAP technology has evolved together with advances in processing, connectivity, and cloud services. For instance, modern OLAP products are not limited by just calculation of aggregates. It can now calculate custom formulas and run driver-based computations which are useful for financial reporting, planning, forecasting, and predictive analytics.
Modern OLAP are also more dynamic. By adding connectivity to data sources, OLAP now provides an up-to-date view of a business – even computing on a real-time basis. It is important to note also that some OLAP are available on the cloud as a service, as more companies move toward a virtualized hosted environment.
Interested in trying an OLAP service in the cloud? Check this out.
OLAP technology falls under the umbrella term “Business Intelligence” which is composed of various tools such as data visualization, and more. BI capabilities are being packaged together with business solutions to provide an analytical perspective of the business.
For example, some eCommerce tools such as those offered by Magento development companies incorporate BI capabilities. You can hire Magento developers and see how the integration of these tools improves the outcomes of the business.
OLAP and Hadoop: A Great Pairing
OLAP continues to be a relevant and exciting technology, most recently in pairing OLAP and Hadoop. As we are OLAP.com, we have ALWAYS seen the value of OLAP technology. We admit OLAP has been a bit out of style the last few years. Some companies even run Google ads about how “OLAP is obsolete,” but nothing could be further from the truth. (Check out our blog on that one.)
We see this in the fashion industry all the time: what is old is new again! This is rare in the technology realm, but it seems to be the case with OLAP. As developers struggle to get value out of Hadoop data, they discovered they needed the speed and flexibility of OLAP. OLAP and Hadoop is a powerful combination for getting to the ultimate goal of extracting value from Big Data.
Bringing OLAP to scale for Big Data
In an article from ZDNet, Is this the age of Big OLAP? Andrew Brust writes about the new relationship between OLAP and Hadoop. He highlights that OLAP technology can be particularly beneficial when working with extremely large Big Data sets. Typically, OLAP has not been scalable enough for Big Data solutions. But OLAP technology continues to progress, we find this new application of OLAP exciting. Brust discusses a few strategies for bringing the two technologies together. He mentions a few OLAP vendors in detail and how they manage the issue of scalability for OLAP software.
If you want to try using OLAP with Hadoop, perhaps you want to give PowerOLAP, the mature OLAP product of OLAP.com, a try? There is a free version of PowerOLAP available. If you plan to test PowerOLAP with your Hadoop, contact PARIS Tech, and they will lift the member limit for you in the free version, as you will need to go beyond the member limit that ships with the free version.
In sum, OLAP.com is pleased to see OLAP rising in relevance once again and getting some of the recognition we felt it deserved all along. It is a testament to the power and value OLAP has as a technology.
The Power of OLAP and Excel
Should Excel be a key component of your company’s Business Performance Management (BPM) system? There’s no doubt how most IT managers would answer this question. Name IT’s top ten requirements for a successful BPM system, and they’ll quickly explain how Excel violates dozens of them. Even the user community is concerned. Companies are larger and more complex now than in the past; they are too complex for Excel. Managers need information more quickly now; they can’t wait for another Excel report. Excel spreadsheets don’t scale well. They can’t be used by many different users. Excel reports have many errors. Excel security is a joke. Excel output is ugly. Excel consolidation occupies a large corner of Spreadsheet Hell. For these reasons, and many more, a growing number of companies of all sizes have concluded that it’s time to replace Excel. But before your company takes that leap of faith, perhaps you should take another look at Excel. Particularly when Excel can be enhanced by an Excel-friendly OLAP database.That technology eliminates the classic objections to using Excel for business performance management.
Excel-friendly OLAP products cure many of the problems that both users and IT managers have with Excel. But before I explain why this is so, I should explain what OLAP is, and how it can be Excel-friendly. Although OLAP technology has been available for years, it’s still quite obscure. One reason is that “OLAP” is an acronym for four words that are remarkably devoid of meaning: On-Line Analytical Processing. OLAP databases are more easily understood when they’re compared with relational databases. Both “OLAP” and “relational” are names for a type of database technology. Oversimplified, relational databases contain lists of stuff; OLAP databases contain cubes of stuff.
For example, you could keep your accounting general ledger data in a simple cube with three dimensions: Account, Division, and Month. At the intersection of any particular account, division, and month you would find one number. By convention, a positive number would be a debit and a negative number would be a credit. Most cubes have more than three dimensions. And they typically contain a wide variety of business data, not merely General Ledger data. OLAP cubes also could contain monthly headcounts, currency exchange rates, daily sales detail, budgets, forecasts, hourly production data, the quarterly financials of your publicly traded competitors, and so on.
You probably could find at least 50 OLAP products on the market. But most of them lack a key characteristic: spreadsheet functions.
Excel-friendly OLAP products offer a wide variety of spreadsheet functions that read data from cubes into Excel. Most such products also offer spreadsheet functions that can write to the OLAP database from Excel…with full security, of course.
Read-write security typically can be defined down to the cell level by user. Therefore, only certain analysts can write to a forecast cube. A department manager can read only the salaries of people who report to him. And the OLAP administrator must use a special password to update the General Ledger cube.
Other OLAP products push data into Excel; Excel-friendly OLAP pulls data into Excel. To an Excel user, the difference between push and pull is significant.
Using the push technology, users typically must interact with their OLAP product’s user interface to choose data and then write it as a block of numbers to Excel. If a report relies on five different views of data, users must do this five times. Worse, the data typically isn’t written where it’s needed within the body of the report. Instead, the data merely is parked in the spreadsheet for use somewhere else.
Using the pull technology, spreadsheet users can write formulas that pull the data from any number of cells in any number of cubes in the database. Even a single spreadsheet cell can contain a formula that pulls data from several cubes.
At first reading, it’s easy to overlook the significant difference between this method of serving data to Excel and most others. Spreadsheets linked to Excel-friendly OLAP databases don’t contain data; they contain only formulas linked to data on the server. In contrast, most other technologies write blocks of data to Excel. It really doesn’t matter whether the data is imported as a text file, copied and pasted, generated by a PivotTable, or pushed to a spreadsheet by some other OLAP. The other technologies turn Excel into a data store. But Excel-friendly OLAP eliminates that problem, by giving you real-time data for a successful BPM system.
To learn more about OLAP, click here.