Our love of data analytics is rooted in our desire to provide meaningful business results through scientific understanding of data. Our desire for analytics is manifested through developing Business Intelligence solutions using Microsoft SQL Server Analysis Services (SSAS).
We utilize Microsoft SQL Server Analysis Services (SSAS) for robust solutions including cubes, data mining, trending analysis and predictive modeling. Each of these Microsoft SQL Server Analysis Services (SSAS) concepts are critical to our implementations.
is a process that involves the interaction of multiple Microsoft SQL Server Analysis Services (SSAS) components. We access sources of data (usually in a SQL Server database but can be any other ODBC or OLEDB data source) to use. We then define data mining structures and models by using SQL Server Data Tools (SSDT) or Visual Studio. We manage data mining objects and create predictions and queries by using SQL Server Management Studio. When the solution is complete, you deploy it to an instance of Analysis Services. Data mining allows businesses to determine relationships among many related or unrelated 'internal' factors such as price, product positioning, or staff skills, and 'external' factors such as economic indicators, competition, and customer demographics. Data mining enables business stakeholders to determine the impact on sales, customer satisfaction, and profits or losses. Finally, it enables users to 'drill down' into summary information to view detail transactional data to follow their finding to their source.
is a way to evaluate the current trend of given values compared to a set of goals. The trend enables the business user to quickly determine whether the value is becoming better or worse relative to the goal. We usually employ visual graphics or indicators with a color or marker to indicate the trend for quick analysis.
involves creating a statistical model of future behavior. Predictive analysis is interrelated to data mining due to convergence with forecasting probabilities and trends. A predictive model is made up of a number of predictors, which are variables and factors that are likely to influence future results or outcomes. With predictive modeling we collect relevant data and compile predictors. We then create a statistical model. Predictions are then made and the model is validated (or revised, continually) as additional data is assimilated. The model may employ a simple linear equation or a complex neural network depending on needs, data, timing and other factors.
Our philosophy on data warehousing is smart. Our philosophy includes the elements of being straight forward, measurable, accurate, analytical, actionable, reliable, repeatable and timely. But out methodology is tenacious. More on that in a minute. For now, here is how our philosophy on data warehousing is smart, actually 'SMAAARRT'.
Here at Leale Solutions our methodology is tenacious. We employ good old fashioned, roll up our sleeves hard work. Dictionary.com defines tenacious as holding fast; characterized by keeping a firm hold, also further defined as highly retentive, persistent. We couldn't agree more and believe this is an accurate word to describe our smart data warehousing methodology. We have a passion for analytics and analytical endeavors. We take pride in our work. We are driven to hold fast and persist in attaining something that is very valued to us. This is first and foremost valuable and meaningful insight into your data. We are tenacious at attaining our goals. Our goals are your goals. Gaining insight into the data that will help your company attains its goals drives our passion for analytics.
The key tools we want to emphasize using are tools for reporting and visualization of your business data. We use any number of tools for the task at hand. These tools include Microsoft SQL Server Reporting Services (SSRS) reports, Excel Pivot tables and PowerBI.
We commonly utilize Microsoft SQL Server Reporting Services (SSRS) to display important information. We utilize this suite of tools to create reports that contain gauges, charts, drill downs, drill through and line item reports which are all interactive. You can read more about our Microsoft SQL Server Reporting Services (SSRS) work here (link to Parameterized SSRS page).
We use Excel Pivot Tables to summarize, analyze, explore and display cube data. While very effective, display capabilities in Excel Pivot Tables are limited.
Power BI for Office 365 is Microsoft's newest cloud-based business intelligence (BI) solution. Power BI launches from within Excel and Office 365 to analyze and visualize data in a 'self-service' way. This tool is designed to help business users gain deep insight. Features include:
Our passion for analytics is brought to life through Microsoft SQL Server Analysis Services (SSAS). We use creative processes, powerful tools, innovative designs and good old fashioned hard work to create solutions that drive deep insight into your corporate data. Our goal is to use this technology to put this data in the hands of your key business decision makers and stakeholders. These tools enable confident and informed decision making. As a member of the Microsoft partner network and you experienced Business Intelligence partner, we have the experience and the experience with the right tools to bring the highest quality results to you and your business.