Self-service Business Intelligence Tools For Reporting On Linux Security Events – With more and more companies requiring their employees to participate in reporting and generating insights, as well as the need to generate insights in a more efficient way, personal productivity tools ( BI)) becomes an important part of every company. data strategy. Now you may be wondering what self service reporting is and how it helps businesses in generating reports.
BI self-service also known as self-service analysis is a tool that allows non-technical employees of an organization to participate in the data analysis process without having to seek help from IT specialists or dedicated data analyst. This is because in the past, before personal BI tools came into play, only users with SQL (data query language) could generate reports, but now anyone can generate insights and collect their data. need less time using simple interfaces. without writing a single line of SQL code.
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So we’ve mentioned a lot the term self-service for BI tools and I’m sure you’re thinking if there are BI tools that aren’t self-service and the answer is yes. The opposite of self-service BI is traditional BI. Users who work with traditional BI Tools are often IT professionals who have extensive SQL knowledge.
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This article aims to highlight the differences between self-service and traditional BI tools and provide an in-depth analysis of the top 5 self-service BI tools on the market so you can make an informed decision about which tool is right for you. most for your business. .
But what exactly is functional analysis? – We wrote about this in detail here: Self-service is a Business State.
Broadly speaking, if you want to decide whether a BI application is self-service or not, you need to evaluate the following:
Self-service reporting should allow everyone to analyze the data they need precisely using drag and drop functionality.
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For a more in-depth comparison, we compare traditional BI and self-service looking at 5 key areas: Application planning, agility, data structure, reporting and data management.
A data governance framework is needed to address concerns about data modeling and storage and user access.
There are certain features that are part of any self-service BI tool regardless of brand. In this section we will explain the most important ones:
Now that we’ve covered the high-level details on self-service BI tools, let’s dig a little deeper into the individual self-service BI brands that have become popular in the market and know better. Start with the first followed by Metabase, Looker, Tableau and Power BI.
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Is a self-service BI tool that focuses on analytics that allows non-technical users to explore data and generate actionable insights without having to use SQL.
Metabase is an open source BI tool best suited for companies looking for a free BI tool to answer their daily analytical questions. However, to answer sophisticated queries, writing SQL queries is a must.
Looker is a cloud-based self-service BI tool from Google that sits on top of your SQL database and helps you model and visualize your data.
Looker is a great self-service BI tool for companies with high budgets that already use the Google ecosystem such as Google Analytics and Google Cloud Platform (GCP) as Looker is easily integrated with these platforms. for advanced use cases such as data import or forecasts.
But for small companies with growing data needs – it may not be the best choice due to the high cost barrier.
Tableau is a powerful BI tool that can be deployed in multiple environments. It is better for companies that have technical resources (Analysts and developers) to correctly configure the platform, modify the data and develop the necessary information for each category.
Lightdash is a new open-source BI service solution that can connect to a user’s dbt project and allow them to add metrics directly into the data processing layer, then create and share insights with the entire team.
Lightdash is certainly promising, but it still has a long way to go to become a complete self-service BI that can meet the needs of business users and data teams.
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At the end of the day, there are hundreds of BI tools on the market and each one offers different features and capabilities. What is important is that you do your homework by reading various articles, forums, user reviews, etc. before choosing a BI application for your organization. Most importantly, if you can get your hands on a free trial version, go for it and test some of your business use cases with the tool to check if it can meet the requirements. This is important to help you make an informed decision.
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Check out this book to familiarize yourself with the ins-and-outs of contemporary analytics.
“I’m surprised to say the following sentence: I read a free ebook from a company and really loved it.” – Data Enginee The feeling you get when you first unlock data’s power is unlike the feeling Prince Adam got when he turned into He-Man. Self-service business intelligence exists to provide this feeling to anyone who wants it by making data easy to use for everyone.
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– from data wizards to the less technical. Seth Rosen, co-founder of Hashpath, recently tweeted that using it as a self-service BI platform was one of the first times he “felt like [he] had superpowers as a data analyst”.
BI-style functionality is indispensable for any company that calls itself “data driven”, thanks to its ability to make data available to everyone. If you’re in the market for a self-service BI platform, here’s what you need to know.
Self-service BI provides business end users (ie, non-technical people) with the ability to analyze data and create insights on their own without the help of technical teams. In contrast, traditional BI tends to require significant technical expertise to use, which can lead to a data bottleneck.
There is no clear line of demarcation between what makes a “self-service” or a “traditional” business intelligence platform. It’s best to think of it as a scene.
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On the one hand, traditional BI platforms require strict control over data. Only a few experts have access to the platform, and the technical know-how to use it properly. As a result, these traditional platforms do not need to invest in use, because their main focus is the ability to choose less to use data.
Here’s an example of creating a SQL query using Situational Analytics, a more traditional BI tool that focuses on the needs of data scientists:
On the other hand, self-service BI platforms prioritize data access. These platforms focus on putting data in the hands of as many people as possible. As a result, self-service BI platforms invest heavily in slick user experience design and code-free features.
When a self-service BI platform does its job well (ie, provides access to data), the impact can be huge. Let’s take a workflow to access data, for example. The easier it is for anyone in your company to use the BI platform, the less you need to go through technical teams (like your data team, IT department, or your developers) to use it. In short, people with no technical background can explore the data on their own.
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This freedom of exploration promotes ad hoc analysis, where you can go where the data takes you without a preconceived idea. Testing on your own means you’re not bombarding your technical team with one-time questions. You can find answers on your own, and the technical team can focus on long-term goals instead of fielding ad hoc questions.
Apply this freedom throughout the company, and you have a true data culture, where data becomes central to daily decision making.
BI self-service has a reputation for giving up strict control in favor of broad access to data. The logic goes: the more people who can use the data, the less control there is over how the data is used. But good self-service tools provide access
Technical teams are the only ones with the skills to effectively use and manage traditional BI platforms. This position of power over data gives these parties strict control over how the company uses the data. But this control comes at a cost – every question, problem and request will have to go through the technical team.
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An example of a self-service BI platform that helps companies maintain control over their data is the ability to manage, create custom programs, and access all information. A system is “a collection of tables and their relationships in your database”.
Simply put, control over your settings means control over the organization of your data. And control over the organization of data means control over how people access that data.
But controlling who has access to what is one piece of the puzzle. You need to be aware of the “data literacy gap” that may exist with self-service BI.
Your technical team is already data literate (go
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