Overview of Yandex DataLens⏱ Estimated read time – 5 min
Let’s take our minds off of the project on receipt data collection for a while. We will speak about the project’s following steps a bit later.
Today we’ll be discussing a new service from Yandex – DataLens (the access to demo was kindly provided to me by my great friend Vasiliy Ozerov and the team Fevlake / Rebrain). Currently, the service is in Preview mode and is, in essence, a cloud BI. The main shtick of the service is that it can easily and handy work with clickhouse (Yandex Clickhouse).
Connection of data sources
Let’s review the major things: connection of a data source and dataset setting.
The selection of DBMS is not vast, nevertheless some main things are present. For the purpose of our testing, let’s take MySQL.
On the basis of the connection created, it is suggested to create a dataset:
On this stage it’s defined which table’s attributes are becoming measurements, and which are turning into metrics. You can choose data aggregation type for the metrics.
Unfortunately, I didn’t manage to discover how it’s possible to state several interconnected tables (for example, attach a handbook for measurements) instead of a single table. Perhaps, on this stage developers suggest us to solve this issue by creating of required view.
Regarding the interface itself – everything is pretty easy and handy. It reminds of a cloud version of Tableau. If comparing to Redash, which is most frequently used in conjunction with Clickhouse, the opportunities of visualization are simply staggering.
Even pivot tables, in which one can use Measure Names as columns’ names are worth something:
Obviously, there is an opportunity to make also basic charts in DataLens from Yandex:
There are also area charts:
However, I didn’t manage to find out how data classification by months / quarters / weeks is carried out. According to an example of data, available in the demo version, developers are still solving this issue by creating additional attributes (DayMonth, DayWeek, etc).
For now, interface of dashboard blocks’ creation looks bulky, and interface windows are not always comprehensive. Here is, for instance, a window, allowing to state a parameter:
However, in the gallery of examples we can see highly functional and convenient dashboards with selectors, tabs and parameters:
Looking forward to fixing of interface shortcomings, improving of Datalens and preparing to use it together with Clickhouse!