8 Best Self-Service Analytics Tools to Unburden Data Engineers and IT Pros In 2024

We'll look at the main features of each tool, its pros and cons, its best use cases, and user reviews to help you make the right choice.

Before we delve into each one, let’s set the tone of what to expect from a good service analytics tool.

10 things you should look for in a good self-service analytics tool

Good self-service analytics tools will have features that unlock many benefits for your organization:

1. Data democratization: This is all about empowering non-technical business users to prepare data sets and perform data analysis on their own. You want a tool that has an intuitive drag-and-drop interface and user-friendly features that help business users build data solutions without programming in Python or SQL.
2. Faster insights: Speed up the data analysis process, enabling quicker decision-making. Best tools offer real-time data analytics for making business decisions under tight time constraints.
3. Data integration: Look for tools that play nice with all your data sources and funnel everything smoothly into your BI platform or data warehouse—without IT help. Check if your chosen tool has pre-built connectors that will help your non-technical users create datasets on their own.  
4. Easy data preparation: Save time with tools that facilitate data cleansing and transformation with no-code transformations and similar features. 
5. Data visualization: Go for tools that not only visualize your data but let you interact with it, enabling you to drill down or up and explore questions in more depth.
6. Advanced analytic capabilities: Look for the ability to extract actionable insights with predictive data modeling and machine learning, enabling you to make data-driven decisions.
7. Collaboration: Choose a tool that enables teams to work together and share insights, fostering collaboration across departmental silos. 
8. Data governance and security: Data security is a must-have with user access controls, encryption, and regulatory compliance. 
9. Ready to scale: As your business grows, your tool should be right there with you, scaling up to match your data
10. Pricing that makes sense: Lastly, you want something that won't break the bank and has clear, straightforward pricing.

So, let's get to it and explore the best self-service analytics options that pack all these punches!

1. Keboola

Best for: Data teams working alongside business users looking for an end-to-end analytics solution.

Keboola is a self-service data operations platform that empowers data teams and business users to connect all company data, automate workflows, and handle all of their data needs. 

Compared to other BI platforms we’ll explore below, Keboola is different due to its ability to automate and save time across all data operations processes. This includes ETL pipelines,  turning data science projects into simple APIs, and providing a platform where business people can get their insights easily, as they would in Excel.

Pricing

Keboola offers a freemium usage-based model. The first month you get 120 minutes of computational runtime for free and then you get an additional 60-minute refill every month. 

If you run out of free minutes, you can buy additional ones at 14 cents per minute.

Unlike many other self-service analytics tools in the field, Keboola’s pricing is fully transparent. They also help you manage your spending by sending automatic messages when you're using your paid minutes. 

Pros 

• Empower both your technical and non-technical users with the tools to self-serve their analytics needs.
• 250+ pre-built connectors to automate data collection and ingestion. 
• Visual flow builder helps you create data pipelines via a drag-and-drop UI.
• No-code and low-code (Python, R, SQL, Julia) transformations help you clean data and compute metrics without advanced coding skills. 
• Data Apps that help you turn raw data into interactive self-service BI tools. 
• Save data engineering time with pre-built data templates that generate datasets in a few clicks.
• Streamline data discovery and increase collaboration with the Data Catalog and shareable templates and code.
• Use data streaming to build a real-time self-service BI solution.
• Scale big data workflows without affecting performance with features like dynamic backend sizing, efficient replication using change data capture, shareable code across data transformations and apps, etc.

Cons

• There are 250+ pre-built connectors available in Keboola, but not all data sources and destinations are covered. If you need to build a custom connector, you can use the Generic Extractor/Writer. The process is straightforward, but it requires some coding skills. 

Reviews 

G2 reviews: 4.7 out of 5 based on 90 reviews

“Keboola helps us save on many fronts: we could let go of many obsolete databases for storage, and we don't need consultants to help develop transformations. We even removed an ad for a data engineer and decided to hire a front-end developer instead, because Keboola is so easy to use that we can achieve more with the existing in-house talent.” -  Ronnie Persson, CTO at Pincho Nation

“If you’re starting a company with a BI or data analytics solution and you’re just figuring out what to do and how to do it, get Keboola. You can build a very complex data or BI solution quickly and relatively cheaply. And Rohlik is proof of that.” - Ondřej Hubálek, Machine Learning Team Leader at Rohlik

2. ThoughtSpot

Best for: Automating insights extraction from a well-modeled data set  

ThoughtSpot is an AI-powered analytics platform that automates the groundwork behind extracting insights using advanced big data techniques. 

Pricing

ThoughtSpot offers a usage-based model. The lowest tier starts at $95/month, but if you want to unlock automated insights (one of ThoughtSpot's greatest advantages compared to other self-service analytics tools), you’ll have to pay $1250/month.

You can try the platform with a 30-day free trial.

Pros 

• ThoughtSpot Sage allows you to search datasets using natural language queries. 
• An input analysis engine that changes the recommendations it serves end users based on what responses they liked.
• Liveboards generate automated real-time interactive dashboards to visualize the insights for you. 
• Automated advanced analytics like outlier detection, correlations between data points, and trend spotting.

Cons

• ThoughtSpot may struggle a little when you have a ton of data or challenging queries. To make it work, it needs to be fine-tuned.
• You need to create data models in your data warehouse before you can tap into its full potential. ThoughtSpot offers some features for data modeling, including the dbt integration, but you’ll have to rely on data engineers or an end-to-end platform like Keboola to sanitize your dataset before you can automate insights extraction.

Reviews 

G2 reviews: 4.4 out of 5 based on 269 reviews

“ThoughtSpot really makes it easier for End-Users to query a Data Warehouse as there is no need for SQL knowledge and Maintainers can set up Worksheets containing all required Joins and even add pre-calculations and additional logic.” - Michael E., Analytic Engineer

3. Tableau

Best for: Enterprises looking for a best-in-class BI tool.

Tableau is an established self-service analytics tool for business intelligence. It helps you automate data visualizations and data analytics. 

They offer two product lines: 

• Tableau Public (free of charge)
• Tableau Desktop (enterprise-ready BI solution)

Tableau also offers adjacent products (charged separately) such as Tableau Server for hosting your datasets on-premise and Tableau Prep for building datasets with advanced tools.

Pricing 

Tableau Desktop is charged by user role. You’ll need either the Creator ($75/month) or Explorer ($42/month) roles to create dashboards, and for each viewer, you’ll have to pay an additional $15/month.

Pros 

• Dashboard personalization and data visualizations that effectively convey the story within your data. Tableau's dashboards are also interactive, making them more engaging for data users.
• Handles complex calculations and generates reports even with extensive datasets. This ensures that data updates remain fast even when you’re dealing with big data volumes. 
• Designed with both technical and non-technical end users in mind. 

Cons

• Tableau Desktop can be an overkill for small businesses.
• The table formatting and sorting features are outdated. 
• Interface can become laggy when working with large datasets or when combining multiple datasets.

Reviews 

G2 reviews: 4.4 out of 5 based on 1949 reviews

“Tableau is the best Enterprise Business Intelligence Tool at being able to build scalable, interactable, robust, dashboards with as many features as needed. It looks like the best and can calculate the right answer if you are good enough with Tableau. It gives beginners the ability to create dashboards but also has the ability to grow and learn and create complex yet simple dashboards as you become an expert. I have been able to create high-level dashboards that drill to the details which is my specialty with great successful results.” - Andrew P., Director, Business Intelligence, Data & Analytics

4. Microsoft Power BI Desktop

Best for: Enterprises with a Microsoft-based data stack looking for a BI tool.

Microsoft Power BI Desktop is one of the most recognized BI tools on the market. The enterprise data analytics platform empowers everyone at the company to make informed decisions with this business intelligence tool.

Pricing 

Power BI has a user license (starting at $15 per user per month) for anyone creating or viewing dashboards within Power BI. Add-ons, like servers for hosting your datasets and computing metrics or additional features, are charged separately. 

Pros 

• The drag-and-drop report canvas is suitable for non-technical business users.
• Copilot AI-driven assistant allows you to use natural language for building and refining dashboards. 
• Virtually unlimited transformation capabilities with its programming language DAX.

Cons

• Runs only on Windows. Companies using other OSs or more open-source data stacks will find it harder to adapt Power BI to their data ecosystem. 
• It offers limited data preparation features. Business analysts can use Power Query to get data from different data sources, but this bypasses company-wide data governance policies and is not ideal. Alternatively, end users can use Dataflows (a new integrated product), but they are quite limited in the data sources they offer.
• All datasets need to be moved to a Power BI instance for data analysis. With big data sets, this can incur additional network and movement costs. 
• Learning DAX can be a steep learning curve.

Reviews 

G2 reviews: 4.4 out of 5 based on 1034 reviews

“Microsoft Power BI is a tool that is easy to use and speeds up data analysis and navigation without the need for technical expertise. It talks to a lot of different data sources, so information can be put on a single site. Power BI's strong visualization tools let users make charts, graphs, and live dashboards that are both visually appealing and help explain results and make decisions.” -  Godfrey C., Technical Quality Manager

5. Qlik Sense

Best for: A team of business users at a scale-up.  

Qlik provides a comprehensive range of business intelligence and analytics tools with its product Qlik Sense. Qlik Sense helps organizations to unify various data sources into a centralized data analytics solution. The solution is anti-query based and positions itself as the analytics platform that can provide insights through clicks. 

Pricing 

Qlik’s pricing is a mixture of user seats (starting at $20 per user per month) and services. To unlock automated reporting and insights, the pricing starts at $2,700/month.

Pros

• Drill-down visual capabilities. Users can click on a chart section or table row and Qlik recalculates dashboards around the surrounding area of interest. 
• Multiple AI functionalities, like automated insights generation, natural language search, and AutoML integration for predictive analytics. 
• Strong automated alerting features that warn you when Qlik detects issues in your data.

Cons

• Doesn’t scale well because Qlik’s performance deteriorates with high data loads, with users complaining about limits with data ingestion and loading. 
• Advanced analytics is limited to what Qlik provides, there is no way to build custom machine-learning models.
• The pricing is prohibitively high for small companies.

Reviews 

G2 reviews: 4.5 out of 5 based on 658 reviews

“The simplicity of Qlik Sense, from both an administrator and end-user perspective, is one of its most striking features. It offers all the features I need to create an easily digestible data visualization that helps find patterns and trends. The visualization tool is one of the best because it is very effective at helping us see all of our data clearly and easily, and because it has many capabilities to maintain the referential integrity of the data.” - Gabrielle S., Media Planner

6. Microsoft Fabric 

Best for: Enterprise teams looking for a self-service tool that brings their existing Microsoft tools (Synapse, Power BI, Data Factory, …) to the next level.

Microsoft Fabric is an end-to-end analytics solution with managed services covering data moving, data storage, data integrations across multiple sources, data science tools, and real-time analytics and business intelligence. It helps you unify data and data operations across disparate tools into a single centralized platform.

Its greatest value shines through when operating within the Microsoft ecosystem of data solutions. 

Pricing

Pricing is complicated for Microsoft Fabric, but it’s always based on a license fee and additional usage charges. Existing Power BI Premium customers can access Microsoft Fabric through the Office store. Alternatively, you can purchase Microsoft Fabric as a pay-as-you-go plan, but the license for the plan depends on the workspace license mode.

Users can try Microsoft Fabric via a 60-day free trial.

Pros 

• A new centralized data repository called a Lakehouse offers the scale of data lakes and the organization of data warehouses.
• AI Copilot feature helps users of any technical level select the “next best” action. 
• Virtual data lake helps you build centralized data models with no data movement.
• Fabric brings proven Microsoft tools under a single roof, from Spark for data engineering to Data Factory for data integration and more. 

Cons

• No support for building and reusing data solutions across use cases and different teams. 
• Lack of data lineage makes data governance and bug resolution harder.
• Business users will find customization hard, the platform requires coding skills for custom data solutions.
• Many features are still in development. However, Microsoft Fabric comes from a renowned company with a proven track record, making the wait worthwhile. But it’s hard to tell until they are actually in general availability.

Reviews 

G2 reviews: At the time this article was written, there were no reviews available.

7. Incorta

Best for: Enterprises looking for a hub to integrate their existing self-service data stack.  

Incorta is an enterprise-ready data analytics platform that helps you integrate multiple tools into a single analytics hub. You can either bring your self-service data stack or rely on Incorta’s basic but solid analytic capabilities. 

Pricing 

Incorta doesn’t disclose its pricing. This means you’ll have to talk to sales to get a bespoke quote. Based on 3rd party offerings, Incorta pricing plans start at $4000/month. But these are surcharges on top of your data infrastructure and tooling costs.

Pros

• A simple yet flexible interface for ingesting data from 200+ databases, applications, and object stores.
• Incorta’s preconfigured Spark clusters for data enrichment and machine learning simplify MLOps for data scientists.
• Data Applications offer many pre-built analytics solutions that accelerate anything from building data lineage graphs from metadata to setting up a modern BI solution for NetSuite.

Cons

• Custom CData Connectors can incur extra costs.
• Integrating third-party tools can be technically challenging.
• Pricing is a limiting factor for small companies. 
• Some users complain that the platform slows down with big datasets, so it’s not ideal for scaling. 

Reviews 

G2 reviews: 4.4 out of 5 based on 54 reviews

“Incorta is an incredible platform that helps us to get in-depth insight and analysis of our overall business operations. It also organizes data analytics for the better productivity of our company. The best part of the platform is that the user does not need coding and technical knowledge for using it.” - Abhishek G., Sales Executive

8. Alteryx

Best for: Data teams in financial services and the public sector.  

Alteryx is an analytics automation platform that offers many features to automate analytical operations. From data integration to preparation (cleaning, enrichment, quality checks) and analysis, Alteryx provides products for each step of the analytic pipeline.

Pricing

Alteryx's basic package starts at $4,950 per user per year (with a minimum of 3 users using the platform), and it includes data integration and data cleaning features. The more advanced features - like Auto Insights, Location intelligence, etc. - are charged separately. 

Pros 

• A drag-and-drop user interface allows users of any technical level to quickly extract, transform, and load datasets.
• Automated data profiling and real-time data inspections allow you to keep an eye on data quality.
• Transformations are performed on sampled data for efficiency before being deployed via cloud technologies over the entire dataset. This saves costs and speeds up data preparation.
• The platform offers many (external) solutions for advanced analytics such as Google Tesseract’s powerful OCR (Optical Character Recognition) for converting PDFs to machine-readable datasets or advanced natural language processing tools to deploy Topic Modeling or Zero Shot Text Classification with no-code solutions.

Cons

• It offers one of the more expensive licenses on the market.
• Some features - especially data integration - require programming knowledge.
• Connecting with external datasets is often slow and buggy.

Reviews 

G2 reviews: 4.6 out of 5 based on 454 reviews

“The interface is easy to use, navigate through and I love its search capabilities. It simplifies the learning curve a bit. Compared to other products I think Alteryx shines in these capabilities.” - Jonathan S., SVP, Risk Analysis Manager

Automate workflows and empower your users with Keboola 

Keboola excels in offering comprehensive end-to-end data solutions for both data teams and business users. 

With automated workflows and AI features, Keboola empowers users to be more independent. They can tap into low-code and no-code features that help them integrate data, prepare datasets for analysis, extract insights, and turn the data into a product.

Give your team a self-service analytics tool that automates the heavy lifting so they can spend more time making data-driven business decisions.

Book a demo with our sales or try Keboola for free (no credit card required).