Business Intelligence

Sifiso W. Ndlovu

Report filtering: Excel slicers vs SQL Server Reporting Services (SSRS) parameters

May 4, 2016 by

At the heart of interactive reporting is the ability for end-users to filter report datasets according to their preference. Therefore, a great data visualization tool is the one that caters for report filtering. Some of the popular data visualization tools used by some of my clients to consume my Business Intelligence solutions usually include SQL Server Reporting Services (SSRS) and Microsoft Excel. Although these tools share a similar publisher, Microsoft, they have several differences on their report usage and configuration. One difference they seem to share is in the way they are configured to enable report filtering, which is the focus of this article.

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Sifiso W. Ndlovu

SQL Server pivoting on non-numeric data types

February 19, 2016 by

Introduction

In the article, Multiple Options to Transposing Rows into Columns, I covered various options available in SQL Server to rotating a given row into columns. One of the options included the use of a PIVOT relational operator. The mandatory requirement of the operator is that you must supply the aggregate function with only a numeric data type. Such a mandatory requirement is usually not an issue as most aggregations and subsequent pivoting is performed against fields of numeric data type. However, sometimes the nature of business reporting requests may be such that you are required to cater for pivoting against non-numeric data types. In this article we take a look at how you can deal with such requirements by introducing a workaround to pivoting on non-numeric fields.

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Sifiso W. Ndlovu

Multiple options to transposing rows into columns

January 4, 2016 by

Introduction

One of the primary functions of a Business Intelligence team is to enable business users with an understanding of data created and stored by business systems. Understanding the data should give business users an insight into how the business is performing. A typical understanding of data within an insurance industry could relate to measuring the number of claims received vs successfully processed claims. Such data could be stored in source system as per the layout in Table 1:

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Steve Simon

SQL Server data mining – How to turn the data into valuable information

June 10, 2015 by

Introduction

In a past chat back in January 2015, we started looking at the fantastic suite of data mining tools that Microsoft has to offer. At that time, we discussed the concept of a data mining model, creating the model, testing the data and running an ad-hoc DMX query. For those folks that may have missed this article, the link may be found immediately below;

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Steve Simon

SQL Server and BI – Creating a query for the revenue projection

June 5, 2015 by

A few days ago I received an interesting challenge from one of our clients. The lady was attempting to estimate her potential monthly revenue recognition for the fiscal year beginning January 1, 2015, through December 31, 2015. The lady named Linda sells goods and services (each class yielding differing sales margins).

In the first portion of this two-part discussion, we shall be looking at the revenue projections for goods.

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Steve Simon

Using the “Row_Number” function and a WHILE loop to create the rolling average report

May 27, 2015 by

Introduction

A few days ago I received an email from a gentleman in the healthcare industry. He had read an article that I had previously published a few years back on a well known SQL Server website. Based on the original article, he requested a few ideas on how to expand the sample code to do a rolling three-month revenue summary, in addition to a rolling three-month revenue average.

In today’s get together, we shall be looking at doing just this!

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Steve Simon

How to import data into SQL Server databases using the OData source for SQL Server Integration Services

April 6, 2015 by

Introduction

A few days back I was looking at ways to access raw data from within Microsoft Dynamics CRM in an effort to extract the raw data and to place it in our data warehouse. I started to explore utilizing OData and SSIS to pull the necessary data from the cloud to our local warehouse.

Whilst there are known authentication issues between Dynamics CRM and the Microsoft OData SSIS data source (and thus we could not utilize this access method), I thought it to be so very powerful, that I began looking for other constructive manners in which to utilize the OData Source.

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Steve Simon

How to automate SQL Server database restores

March 30, 2015 by

Introduction

A few days back I encountered an interesting challenge. The client wanted to have copies of the nightly backups of the transactional databases restored on a warehouse server, to be utilized to update the warehouse.

The over all process

Prior to the pushing the daily backup to the warehouse server, the previous days restore is deleted. The important point being that the “SQLShackFinancial” database is no longer present on the warehouse server. Having been deleted, downloading of the backup file begins and the restore of the current backup version begins. Normal warehouse processing then ensues and so the cycle continues.

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Johan Ludvig Brattås

Performance tuning an SSAS Tabular model

March 19, 2015 by

Modeling for the xVelocity/Vertipaq engine is a completely different beast than modeling for your trusty multi-dimensional SSAS cubes.
In-memory = blazingly fast; At least that’s what you would think.
As Tabular models gain popularity with business users and developers alike, we’re starting to see that this isn’t always the case.
We’re going to take a look at some of the common errors and mistakes and how to avoid them.
And since the PowerPivot engine is the same – you will learn how to tune your PowerPivot-based Excel workbooks as well.

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Steve Simon

Which Reporting Services dataset fields are being utilized by the reports?

March 18, 2015 by

Introduction

Have you ever felt like pulling your hair out, trying to ascertain exactly which fields in your existing Reporting Services datasets are being utilized by your reports. This happened to me recently during a corporate conversion and cleanup exercise for a database migration to the cloud.

The “aha moment came after having presented a paper at the PASS SQL Server Nordic Rally (March 2015), when one attendee came up to me and asked if I knew of a method to do this. As they say ‘necessity is the mother of invention’ and spiking my interest, I played around until I came up with the solution that we are going to chat about today. The end solution may be seen below

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Steve Simon

How to convert data format into a valuable dataset using SQL Server Reporting Services

March 16, 2015 by

Introduction

Oft times we are forced into situations where we must clearly think outside of the box. In today’s “get together”, we are going to discuss a challenge that I encountered during the last week of February of this year. The client had been charting weekly business calls placed by his sales reps. Our client had been tracking these results within an Excel spreadsheet (see the screen dump below) and he would be using this spreadsheet to report the sales reps progress going forward. My task was to source this data for the corporate reports in Reporting Services, from this spreadsheet and do so on a weekly basis. The client, being resistant to change, was not willing to change the format of the spreadsheet to something more conducive to be utilized by the chart that he wished to produce (see immediately below).

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Steve Simon

Reporting in SQL Server – create a matrix based sub-report called by the previously created main report

March 4, 2015 by

Introduction

As you will remember from our last “get together” we created an application that permitted us to report upon financial data based upon an unorthodox financial year. In fact, our fiscal year started in July and ended in June. We created a chart to display the data.

In today’s “get together” we are going to push our application a bit further and build in a subreport which will bring up the underlying data when the end user clicks upon the chart for any particular month. Thus should the user click on February 2015, then all of February’s data (for the selected funds) is shown in a matrix. If the user chooses March, then March’s data is shown.

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Steve Simon

Reporting in SQL Server – create a chart based on the data extracted for a given date range

February 27, 2015 by

Introduction

I recently heard from a lady from overseas who wanted to find a quick and dirty mechanism of extracting data for a given date range (based upon a fiscal year that started July 1st and ended June 30th). The idea interested me and as always, I had to try it out.

In today’s “get together”, we are going to have a look at how this may be achieved.

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Steve Simon

Using a cursor to correctly extract SQL Server data and place it in a Reporting Services matrix

February 23, 2015 by

Introduction

In our last two chats, we discussed enterprises that have had financial years that began in July and ended at the end of June. One of our clients works with this fiscal calendar and their financial folks are Excel “Fundi’s” (Fundisa is a Nguni word for “expert”). Many of their reports contain the current month’s sales, in addition, carrying running totals from the beginning of the fiscal year to date. Read more »

Steve Simon

Using Master Data Services in SQL Server to quickly create a GUI that may be maintained by the end user

February 20, 2015 by

Introduction

Oft times we are forced into situations where we clearly need to think outside of the box. A case at hand arose early in 2014 where one of our client’s required a “quick and dirty” front end to modify data within a table that reflected the outstanding balances (of their clients) and the attempts that they had made to recover these funds. Master Data Services seemed to be the way to go!

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Steve Simon

Monitoring SQL Server Reporting Services

February 19, 2015 by

Introduction

In our last get together I mentioned that oft times SQL Server reports are created due to a dire business need to be used once and never again. Further, some reports that we believe are not often used could be “top of the pops” unbeknown to us. A guess as to a number of times a report is used per month, in addition to the statistics behind each report should not be guesswork, but rather monitored actively to ensure that frequently used reports are both efficient and effective. Further, those reports that are either not used or have not been run in quite some time, should perhaps be removed in order to keep the server clean and not cluttered.

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Steve Simon

Creating dynamically generated CSV files containing SQL Server data

February 12, 2015 by

Introduction

A few months back, I presented a paper at SQL Saturday 327 in Johannesburg, South Africa. Late last month I received an email from one of the attendees. His issue was quite interesting and I decided to share it with you. The gentleman wanted a SSIS script that would permit him to extract data from a SQL Server database table and place it in a CSV file with a dynamically allocated name. Being a strong advocate of using the SSIS toolbox, I experimented with an alternative solution. We are going to construct THIS SOLUTION in today’s get together.

Let’s get started.

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Steve Simon

SQL Server Reporting Services Best Practices

February 11, 2015 by

Introduction

In past chats, we have had a look at a myriad of different business intelligence techniques that one can utilize to turn data into information. In today’s “get together” we are going to try to pull all these techniques together, rationalize our development plans, and moreover, look at some good habits to adopt or for the want of better words utilize SQL Server Reporting Services Best Practices.

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Steve Simon

Getting started with data mining in SQL Server

January 19, 2015 by

Introduction

In past chats, we have had a look at a myriad of different Business Intelligence techniques that one can utilize to turn data into information. In today’s get together we are going to have a look at a technique dear to my heart and often overlooked. We are going to be looking at data mining with SQL Server, from soup to nuts.

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