Database administrators have a lot of tasks and responsibilities but perhaps the most challenging task is performance tuning. Because performance tuning issues can cause huge problems in the business area, database administrators have to monitor performance metrics and have to get immediate, if not sooner, notifications when the performance values cross an optimal state. Generally, this notification comes by e-mail.
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In this article, we will discuss the SQL Server Reporting Service Report Builder and look at how to handle common client, end user requests using Report Builder. Report Builder is a very powerful tool to create a report for the SQL Server Reporting Service.
Advantages of the Report Builder is that it:
In this article, we will discover how to find the associations and hidden patterns in a dataset. The tool we will use for this is Power BI and not use any statistical functions or calculation.
Power BI is one of the most powerful business intelligence solutions in the market. A cloud-based, user-friendly interface and basic development abilities provide this solution to be more convenient for people to use.
As you may know, Microsoft now supports R script in SQL Server and Power BI. R script support opens magical gates of statistics world to Power BI. Custom Visual offers very useful and interesting visual components for Power BI. In this store, many useful visualizations have been created by Microsoft or the community itself. Some of these visuals use R script infrastructure and this feature allows us to create advanced visual analytic in Power BI. Only a Power BI account is enough to connect and download theses visuals. We will use these visuals in our examples.
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In this article, we will discuss the k-means algorithm and how can we develop a k-means model on Azure Machine Learning Studio.
Machine learning is an area of artificial intelligence that helps us develop relationships between data and predict the future. There are many secrets that are hidden in the data. To discover these secrets, we need Machine Learning algorithms. Machine learning plays the key role in leveraging existing data to exploit business opportunities.
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Good, clean and reliable data is important for every company, because well-analyzed data will open new possibilities to success. When we look at successful companies, we see that they’ve analyzed customers, sales, and finance data very well. At this point, a game changer enters: machine learning.
Machine learning is a type of artificial intelligence which analyzes data in order to predict future and discover hidden patterns. The output helps us make decisions. Machine learning is widely used in finance, healthcare and marketing.
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One of the main tasks of a SQL Server database administrator is performance tuning. Sometimes, though, coders or developers don’t always prioritize database performance or query optimization. Here is a typical scenario
Graph database
A graph database is a type of database whose concept is based on nodes and edges.
Graph databases are based on graph theory (a graph is a diagram of points and lines connected to the points). Nodes represent data or entity and edges represent connections between nodes. Edges own properties that can be related to nodes. This capability allows us to show more complex and deep interactions between our data. Now, to explain this interaction we will show it in a simple diagram
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In the first part of this article, we will discuss about parallelism in the SQL Server Engine. Parallel processing is, simply put, dividing a big task into multiple processors. This model is meant to reduce processing time.
Execution plans are the equivalent to highways and traffic signs of T-SQL queries. They tell us how a query is executed.
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R is a very popular data programing language. R is especially used in data analysis, statistics calculations, predictions, data mining and machine learning. R is used by data scientist, economist, genetic scientists, and statisticians. R has very wide usage in real life. Healthcare, finance, marketing, and manufacturing are some of them.
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