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Shared data model for PowerBI and other reporting tools

Introduction

There are many tools on the market which provide us multiple ways of creating reports. It’s common that a company “A” prefers one reporting solution over the other, while company “B” has a completely opposite experience. The same goes for people – we also have our favorites – one wants to see a report prepared with PowerBI while the other would like to use Excel, simply because knows it better.

Every time we need a report we need to prepare data first. Analytical and data visualization tools are different and require different skills to prepare data for reporting or analysis. It costs time, requires a tool-specific knowledge and of course provides redundant work in a layer between a data source and a reporting tool. How about having the shared data model prepared beforehand with a data virtualization tool like Querona and reused?

Let’s have a look first at how it can look like when the whole setup is done with PowerBI. Then we will try to the same but with Querona as the virtual data layer.

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Data anonymization for cloud and on-premise databases

The case

When the cloud computing is concerned we used to think about rapid elasticity, resource pooling or broad network access. All the points are valid but what about security? Is it really safe that data is loaded somewhere off the premises? Are all the legal rules met as well?
Querona supports many nice features which are welcome and even surprising. One of such features is data anonymization. Read more

Security of data in Querona virtual databases

Introduction

Applying strict security rules in one of the oldest known problems in IT. Nowadays it is especially important because data leaks have grown to become one of the biggest challenges for modern companies, often resulting in significant financial losses.

Data security in Querona

Querona comes with easy to use mechanism for ensuring data security in both a column-based and a row-based manner using arbitrary rules. As an example, we will show how to limit data visibility based on the role assigned to the given user. Read more

Windows Integrated Security and Apache Spark using Querona as a proxy

The case

Modern data warehousing solutions are often highly distributed and cloud-based. Users, usually authenticated via security mechanisms available in solutions like Active Directory, should have secure access to the data warehouse or a Data Lake, hosted anywhere and on any platform (Windows, Linux).

Technologies like Apache Spark or Microsoft Azure HDInsight do not provide an easy way to configure use of Windows Integrated Authentication (WIA). Some other data sources do not support WIA at all.
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How to integrate disparate data sources in 10 minutes

Increasingly common, innovative business projects have a need to integrate various databases to extract information. Those of us, who were in the industry for long enough, have seen it all. Relational and non-relational databases, CSV or Excel files. Most probably, those sources were not even designed to be used together.

Traditionally, some kind of ETL project had to be created. It would load the data into “stage” tables, apply necessary transformations (like data type unification), and finally load the data somewhere. Time of the project would be measured in days or weeks rather than hours.
Moreover, qualified staff is required, with knowledge about all source systems and the destination system. Read more

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