Magic Quadrant for Business Intelligence and Analytics Platforms

According to a recently published Gartner report, by 2018:
  • Most business users and analysts in organizations will have access to self-service tools to prepare data for analysis as part of the shift to deploying modern BI platforms.
  • Most stand-alone self-service data preparation offerings will either have expanded into end-to-end analytical platforms or been integrated as features of existing analytics platforms.
  • Smart, governed, Hadoop-based, search-based and visual-based data discovery will converge in a single form of next-generation data discovery that will include self-service data preparation and natural-language generation.
During the past several years, the balance of power for business intelligence (BI) and analytics platform buying decisions has gradually shifted from IT to the business as the long-standing BI requirement for centrally provisioned, highly governed and scalable system-of-record reporting has been counterbalanced by the need for analytical agility and business user autonomy.

 The evolution and sophistication of the self-service data preparation and data discovery capabilities available in the market has shifted the focus of buyers in the BI and analytics platform market — toward easy-to-use tools that support a full range of analytic workflow capabilities and do not require significant involvement from IT to predefine data models upfront as a prerequisite to analysis.
The shift in the BI and analytics market and the corresponding opportunity that it has created for new and innovative approaches to BI has drawn considerable attention from a diverse range of vendors. The list spans from large technology players — both those new to the space as well as longtime players trying to reinvent themselves to regain relevance — to startups backed by enormous amounts of venture capital from private equity firms. A crowded market with many new entrants, rapid evolution and constant innovation creates a difficult environment for vendors to differentiate their offerings from the competition. However, these market conditions also create an opportunity for buyers to be at the leading edge of new technology innovations in BI and analytics and to invest in new products that are better suited for Mode 2 of a bimodal delivery model than their predecessors.
Gartner's position is that organizations should initiate new BI and analytics projects using a modern platform that supports a Mode 2 delivery model, in order to take advantage of market innovation and to foster collaboration between IT and the business through an agile and iterative approach to solution development. The vendors featured in this year's Magic Quadrant present modern approaches to promoting production-ready content from Mode 2 to Mode 1, offering far greater agility than traditional top-down, IT-led initiatives — and resulting in governed analytic content that is more widely adopted by business users that are active participants in the development process. As the ability to promote user-generated content to enterprise-ready governed content improves, so it is likely that, over time, many organizations will eventually reduce the size of their enterprise system-of-record reporting platforms in favor of those that offer greater agility and deeper analytical insight.
Source: Gartner, 2016

Comments

Post a Comment

Popular posts from this blog

EOQ Calculations in Excel

Image
Last week in Operations Management we used Excel to calculate the Economic Order Quantity and graph Carrying Costs, Ordering Costs, and Total Costs. The Economic Order Quantity or "EOQ" is the order size that "minimizes" Total Costs. Any more or less and you are spending too much on ordering or too much on keeping inventory. For example, in the Excel spreadsheet below, if you had an Annual Demand of 12000 units, Ordering Costs of $10 per order, and Holding costs of $4 per unit per year, the EOQ would be 245 units and Total Costs would be $980.00: We used the following formula in Excel to calculate EOQ: =SQRT((2*B2*B3)/B4) And the following formula to calculate Total Costs at this point: =$B$6/2*$B$4+$B$2/B6*$B$3 To create the graph, we used the following formulas and simply copied them over a range of 100 to 500 units. Ordering Costs: =$B$2/D2*$B$3 Holding Costs: =D2/2*$B$4 Total Costs: =F2+G2 Looking at this chart, we can clearly see that our order size of 245 is ...
Read more

Reliability Calculations in Excel

Image
In Operations Management today we used Excel to calculate product reliability. Reliability is defined as "the ability of a product, service, part, or system to perform its intended function under a prescribed set of circumstances" (Stevenson, 2009). In order to calulate reliability over a given length of time we need to use the following formula: P(no failure) = e -t/MTBF where: e = 2.7183 t = Length of service before failure MTBF = Mean Time Between Failures One of the cases we did in class involved an auto detailing company that wanted to calculate the reliability of its vacuum cleaners. Excel provides an "EXP" funtion that we can easily apply here. After entering all data for the problem as shown on the spreadsheet below, we type the formula =EXP(-A5/$B$2) in cell B5 and copy down. Next we plot the distribution for t=0 to the maximum life expectancy of 20 years using a line graph. What we end up with looks like a classic case of "ex...
Read more

“How Are We Doing?” Efficiency, Utilization, and Productivity

Image
In business, knowing how we are performing in relation to our competition is vital. Internally we want to know if we are using resources effectively and getting the most out of what we have. Efficiency and Productivity are two calculations that are fundamental to the success of any organization. While the calculations are simple, choosing what measures to use and collecting the necessary data requires a thorough understanding of your industry. To calculate Efficiency you will have to first decide what to use as a base for comparison. Does your company already have a “target” of some kind? Like total units produced? If so then you can compare everything to that. Once you have that, there are a couple of basic formulas that can be used: Efficiency = Actual Output/Effective Capacity X 100% Utilization = Actual Output/Design Capacity X 100% Design Capacity is the maximum output achieved under ideal conditions. Effective Capacity is always less than Design Capacity because of factors...
Read more