Microsoft SQL Server Analysis Services

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.

Data Mining

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.

Trending Analysis

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.

Predictive Modeling

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.

Cubes, Measure, Dimension & Facts

Cubes

Cubes are a set of related measures and dimensions that are used to analyze data.

Measure

A measure is a fact, which is a transactional value or measurement, these are commonly aggregated. Measures are usually derived or sourced from columns in one or more source tables, and are grouped into 'measure groups'.

Dimension

A dimension is a group of attributes that represent 'data interest' areas related to the measures, and which are used to analyze the measures in the cube. Attributes are sourced from columns in one or more source tables. The attributes within each dimension can be organized into hierarchies to provide paths or drilldowns for analysis. Cubes are then augmented with calculations, key performance indicators (KPIs), actions, partitions, perspectives, and translations. A cube is essentially synonymous with a Unified Dimensional Model (UDM). Using Microsoft SQL Server Analysis Services (SSAS), cubes are developed based on tables and views that are modeled in a data source view.

Facts

Facts in a cube are aggregated across dimensions, based on the dimension hierarchies.

Philosophy

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'.

Straight forward

Our data warehousing philosophy is straight forward. We as a company and fellow stakeholder are straight forward. This is really two fold. First, we shoot it straight. We are honest about the tasks that need to be accomplished. We are transparent about what we can and cannot use from your enterprise data. We will provide a straight forward assessment of our findings. Second, we are forward. We here at Leale Solutions are forward looking and thinking. We are most interested in defining your requirements and making those a reality. The rearview mirror is important because it shows where we came from but it is very small in comparison to the size of the windshield.

Measurable

Our data warehousing philosophy is rooted in the goal of measurement. Measurement is much different than reporting. Reporting is the first step but generally stops there. Measuring is the act of comparing values to inputs. This comparison is at the root of analytics.

Accurate, Analytical and Actionable

Accuracy is at the base of all of our reporting and measuring activities. If the data is not accurate the results based on that data will not be accurate. Our goal is to provide the most accurate data, reporting and measurements possible. We have enough industry experience to know that in some cases, data accuracy can never be 100%. In these instances we provide a confidence number as well. This confidence value is an indicator highlighting our confidence of the underlying data. Again, our goal is to provide the most accurate data, reporting and measurements possible. When this is not possible, the data can still be extremely valuable and we will provide solutions.

The data warehousing philosophy we employ is analytical. We use a philosophy that breaks complex concepts into basic components for ease of use and understanding. We understand that your data can be complicated. We here at Leale Solutions also have the experience to know how to handle complicated data and data systems. As the old riddle goes, 'How do you eat an elephant?' The answer of course is one bite at a time. I'm certainly not condoning eating elephants. In fact, we have no elephant eating experience. However, the premise hits extremely close to the point we are trying to make. The detailed breakdown of complicated concepts into basic elements is the definition of analysis. Our analytical philosophy is born of this. Once we break out the concepts we can readily create solutions to make sense of your data.

The data warehousing philosophy we employ is actionable. Our philosophy dictates that we have purpose in our actions. We provide analytics that your business can use to take action. We provide deep insight into opportunities that are beneficial for your business. These include opportunities that were not previously realized, deep cost savings and new options for business potential. Deep insight into the data your business captures can provide your business with more opportunities, some known, and perhaps some unknown.

Reliable and Repeatable

Reliability is a prerequisite of our philosophy. Reliability is extended to both the reports and display of data and the platforms and tools that we employ to deliver and display these reports. Reporting and analytics need to be reliable. These items need to be available at all times with no intervention of staff or manual steps. Our solutions do not require waiting on the 'database guy' to run some behind the curtain magic. We have combined decades of experience with the platform that runs our SSAS implementations. Microsoft SQL Server Analysis Services (SSAS) is rock solid and reliable. Our experiences of tuning and honing our craft will keep it that way.

Repeatability is a foundation level requirement in our philosophy. The ability to run reports and get accurate results must happen over and over again. Results that do not change over time is paramount. Again, these items need to be available at all times with no intervention of staff or manual steps. Our solutions do not require waiting on the 'database guy' to run some behind the curtain magic. These are repeatable when you need them, every time.

Timely

Our philosophy dictates that we provide your business with timely solutions. This includes business intelligence solutions that provide you with insight and solutions before you ask for them. What is better than on time? Early. What is better than early? Before you even ask. How can we deliver solutions before you might ask? The answer is rooted in data mining and analysis. In most environments, data mining is an extremely powerful tool that allows business users to gain deep insight into their own data to find trends, markers and key elements that create the justifications for changes and adaptations to allow your business to attack new opportunities and even sharpen the approach to opportunities in which you are already engaged.

SQL Server Analysis Services

Methodology

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.

Tools

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:

  • Power Query: Enables business stakeholders to easily search and access public data and the enterprise data, all within Excel.
  • Power Map: This is a 3D data visualization tool for mapping and interacting with geographic and temporal data.
  • Power Pivot: This is for creating and customizing flexible data models within Excel.
  • Power View: This is for creating interactive charts, graphs and other visual representations of data.

Final Thought

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.

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