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It’s such an honor that I’m invited to speak in Pass Business Intelligence Virtual Chapter webinar which will be held on 23 Jan 2016. Agenda: Introduction to Power BI … Continue reading Webinar: Visualising Your Azure SQL DataWarehouse with Power BI. I would be very happy to have you all in the webinar.
It’s such an honor that I’m invited to speak in Pass Business Intelligence Virtual Chapter webinar which will be held on 23 Jan 2016. Agenda: Introduction to Power BI … Continue reading Webinar: Visualising Your Azure SQL DataWarehouse with Power BI. I would be very happy to have you all in the webinar.
In the previous post I announced that I will speak in “Visualising Your Azure SQL DataWarehouse with Power BI” webinar on 23 Jan 2016. The webinar host was Pass Business Intelligence Virtual Chapter. It was such an amazing experience for me to speak in the webinar and I would like to thank all 105 attendees.
In the previous post I announced that I will speak in “Visualising Your Azure SQL DataWarehouse with Power BI” webinar on 23 Jan 2016. The webinar host was Pass Business Intelligence Virtual Chapter. It was such an amazing experience for me to speak in the webinar and I would like to thank all 105 attendees.
I look forward to another rewarding experience at the 2016 Summit. Since I couldn’t be in two places at the same time, I tried to make the choices that were most relevant to our team, our customers and our partners, and I chose the following sessions.
I look forward to another rewarding experience at the 2016 Summit. Since I couldn’t be in two places at the same time, I tried to make the choices that were most relevant to our team, our customers and our partners, and I chose the following sessions.
Do We Still Need a DataWarehouse – Roxanne Edijali. Navigating the Data Lake – Adam Ronthal. Interactive Visualizations for Everyone – Rita Sallam. Big Data Discovery – Rita Sallam. I look forward to another rewarding experience at the 2016 Summit.
In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to datawarehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.
In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to datawarehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.
In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to datawarehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.
2012: Amazon Redshift, the first of its kind cloud-based datawarehouse service comes into existence. Fact: IBM built the world’s first datawarehouse in the 1980’s. Microsoft also releases Power BI, a datavisualization and business intelligence tool. There is Alibaba Cloud, Turbonomic, Terremark etc.
It was lately revised and updated in January 2016. 8) Data Smart: Using Data Science to Transform Information into Insight, by John W. Best for: a somewhat technical reader who is good with Excel, but doesn’t know much about data science. Khan Analytic Philosophy: A Very Short Introduction by Michael Beaney.
If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. The ElegantJ BI Advanced Data Discovery, Smarten approach to BI tools, includes Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart DataVisualization.
If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. The ElegantJ BI Advanced Data Discovery, Smarten approach to BI tools, includes Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart DataVisualization.
If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. Data Access. Data Sharing and Reporting. Our second article in this series is entitled, ‘ Guarantee BI Success: Achieve! Accomplish! Do it Right!’
Consider advanced analytical requirements like Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart DataVisualization. When your organization can dive deep into data and spot trends and patterns, your team will gain valuable insight into the market, the competition and buying behaviors.
Consider advanced analytical requirements like Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart DataVisualization. When your organization can dive deep into data and spot trends and patterns, your team will gain valuable insight into the market, the competition and buying behaviors.
Consider advanced analytical requirements like Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart DataVisualization. When your organization can dive deep into data and spot trends and patterns, your team will gain valuable insight into the market, the competition and buying behaviors.
With widely used versions like Crystal Reports 2016 and its server editions anticipating losing support on December 31, 2027, and Crystal Reports 2020 scheduled to end support by 2026, you’re left with limited time to determine how to move forward without disruptions to your business intelligence workflows.
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