What Is Data Mining?
This is a comprehensive article detailing data mining, its application, and importance to businesses.
Location: Remote Time: 10:30am – 7:30pm Contract: 6months SSIS Developer Skills / Experience: Required skills: • Must have 6+ yrs of experience in Business Intelligence development/integration or with SQL server development. • Min 2yrs hands-on experience in developing SSIS packages. • Capable and willingness to work single handedly on implementing SSIS solutions. • Must have exposure to at least 1 end-end solution design using SSIS. • Should have experience working with PL/SQL procedures and commands. • Should have a strong experience in SQL Server. • Should have excellent understanding of MS SQL Server & Data Warehousing architecture. • Should have good understanding of business processes and functional programming. • Good communic...
Project requirement 1) you will get SEVERAL Excel files that contain US-based addresses (see attachment as one example) 2) we need your help to map those US-based addresses onto a US map using BI tools (e.g., Tableau) or other tools you can think are appropriate. Each address should be represented as a circle or a dot 3) in some cases, we need you to use red circles/dots to represent one group of US-based addresses, and blue circles/dots to represent another group of US-based addresses
I’m looking for someone to write an enticing synopsis of my business and territory for potential buyers.
ready-made power bi dashboards for oracle EBS finance & supply chain
Buenos días, El objetivo del proyecto es resolver ejercicios teóricos de Ingeniería de datos (Microsoft SQL Server), business intelligence y power bi. Son 20 preguntas sobre el tema. Por favor enviar propuestas solo personas de habla hispana y que tengan dominio del tema.
This is a comprehensive article detailing data mining, its application, and importance to businesses.
Is your job going to survive this age of automation? Yes or no, here are some tips to ensure your survival.
This is a detailed article on how to avoid failures in execution of big data analytics projects.