Tag: lytix

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF) [Part III]

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF) [Part III]

In this final blog, we discuss the measures that have to be made. Note: this is the third part of the blog. Missed the second part? Read it here. Calculations From here on out we will continue with all the calculations that have to take place to get to the end result of the time aspect of OTIF. […]

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF) [Part II]

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF) [Part II]

Bringing everything together in one table Note: this is the second part of the blog. Missed the first part? Read it here. Step 1 Select the new Orders table you just made and click “Append Queries as New” Now append the newly created Orders table with the newly created Deliveries table If  you have more than 2 tables […]

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF)

Lesson learned at the customer: Merging two tables to calculate On Time In Full (OTIF)

It’s always fun to make your customers happy and learn new stuff by simply just doing your job. That’s what we did at one of my customers lately. Us and a colleague (at the customer) figured out a way in Power BI to calculate the OTIF over multiple fact tables. For both beginner and intermediate […]

Kimball in a data lake? Come again?

Kimball in a data lake? Come again?

Introduction Most companies are already familiar with data modelling (be it Kimball or any other modelling technique) and data warehousing with a classical ETL (Extract-Transform-Load) flow. In the age of big data, an increasing number of companies are moving towards a data lake using Spark to store massive amounts of data. However, we often see […]

Process Mining, the pounding heart of the intelligent enterprise

Process Mining, the pounding heart of the intelligent enterprise

Process Mining provides you with an objective and quick diagnosis on the actual execution of your business processes by extracting the necessary information from your IT systems. In the past this was a tedious task based upon lots of interviews and in more than 98% a misrepresentation of reality. Process Mining removes this unreliability of this tedious task […]

Power BI: Paginated Reports

Power BI: Paginated Reports

One of the most valuable, yet less used functionalities of Power BI is ‘Paginated Reports’. This article will explain what they are, when you need to use them and how they can benefit your organisation. At the end, some samples can be downloaded that demo the functionality.  Starting-Off with an Example As you can see […]

Transfer learning in Spark for image recognition

Transfer learning in Spark for image recognition

Transfer learning in Spark demystified in less than 3 minutes reading Introduction Businesses that want to classify a huge set of images in batch per day can do this by leveraging the parallel processing power of PySpark and the accuracy of models trained on a huge set of images using transfer learning. Let’s first explain […]

Premium Per User (PPU) explained

Premium Per User (PPU) explained

Just last week, the Power BI CAT team extended their current licensing model with the release of Premium Per User (PPU) under public preview. On what ground exactly do current licensing models differ from this new release? We’re reaching our next destination: Premium Per User! What Power BI licensing offerings Microsoft already had in store? First […]

Things to consider when creating a Data Lake

Things to consider when creating a Data Lake

Have you wondered what a data lake is? What are typical use cases for this lake? How can you benefit from a data lake are? In this blog post, we will show you the added value of a data lake while pointing-out some pitfalls and best-practices. Before diving into data lakes (ba-dum-tsss), let us start […]

Azure Synapse Analytics

Azure Synapse Analytics

Organizations understand the value of data more than ever. A Data Warehouse as a single source of truth, a data lake to store data for analytical exploration, self-service tools for data transformation, visualisation, and consumption as well as clusters to process immense data volumes. All these different use cases require other specialised tools resulting in […]