49,378 Companies
- United States: 10,750 Companies
- North America: 13,215 Companies
- EMEA: 19,041 Companies
- United Kingdom: 3,391 Companies
- APAC: 9,272 Companies
- Australia and New Zealand: 1,719 Companies
(MSPs, CRM Vendors, Resellers, ISVs, CRM Software Companies) in our database across the globe
What are Data Preparation Tools?
Finding, combining, cleaning, manipulating, and sharing curated datasets for various data and analytics use cases, such as analytics and business intelligence (BI), data science and machine learning (ML), and self-service data integration, is done through the iterative and agile process of data preparation. By empowering business users such as analysts, citizen integrators, data engineers, and citizen data scientists to combine internal and external information for specific use cases, data preparation technologies promise faster time to delivery of integrated and curated data. The data quality of the users' discoveries can also be improved and reviewed, and anomalies and trends can be found and identified. Certain recurrent and tedious data preparation processes can be enhanced by machine learning (ML) methods, and in certain situations, they can even be fully automated.
1. Alteryx
The main analytics and data science platform of the business is Alteryx Designer. Data from data warehouses, cloud apps, spreadsheets, and other sources may be connected to and cleaned up using the tool's simple user interface. Users can make use of the features for data integration, quality control, and transformation. For the purpose of combining spatial data files with external data, such as demographics, Alteryx Designer also offers data blending.
2. Microsoft Power BI
A business analytics tool for data visualization, analysis, and sharing is called Microsoft Power BI. Through the use of simple real-time dashboards, it provides company monitoring for quick and informed decision-making. Users can create stunning visuals using Microsoft Power BI that can be shared with team members on a variety of devices. It makes it possible to visually explore and analyse the data both locally and remotely. Interactive data reports and user-created dashboards can be shared and used for user collaboration.
3. Flatfile
The data onboarding technology from Flatfile guarantees that data can be imported by businesses easily, rapidly, and in a clean, useable state. Users can match incoming file data with target data models you've specified for data validation after ingesting CSV or XLS files. Flatfile learns how data should be arranged over time with features like automated column matching recommendations, which helps make the data onboarding process for your clients more effective. Control over data formatting is given through the flatfile validation features.
4. Talend
Talend is another well-known solution for data preparation that makes use of machine learning algorithms to investigate, clean, standardise, recognise patterns in, reconcile, etc. To assist users in the data preparation process, this programme offers automated suggestions. Talend also provides governance through masking rules, role-based access, and workflow-based data curation. Users can also exchange databases and preparations, or they can include data preparations into batch, bulk, and real-time data.
5. Tableau
Customers can better understand their data thanks to a direct and visual interface, clever features that make data preparation simple, and integration with Tableau's analytical workflow that speeds up the time to insight. Connect to data in a database or a spreadsheet, on-premises or in the cloud. Without writing code, access, integrate, and clean dissimilar data. For improved business outcomes, friction can be reduced by making sharing simple and bridging the gap between data preparation and analytics. Tableau Prep makes data preparation at scale possible for more individuals in your company than ever before by using visual feedback.
6. Datameer
DataMeer is a SaaS-based platform for data preparation. Datameer purifies data by locating duplicates, outliers, and inconsistent values as well as missing values, blanks, and nulls. Additionally, it makes advantage of the formula builder to find complex patterns in the datasets. Additionally, it makes it easier to combine structured and unstructured data. It has a union feature that appends datasets to one another without regard to cardinality. Column splitting, statistical grouping, column and row pivoting, advanced text parsing, path construction, if and comparison operations, as well as time, date, and text manipulation capabilities are some of the features for data transformations it has.
7. SAP
SAP is a flexible data preparation solution that supports master data management (MDM) projects, precise analytics, and data migration. Self-service data preparation software called SAP offers the option of both on-premises and cloud deployment. Through the discovery and exchange of data from multiple sources, it improves the utility and quality of the data. Additionally, SAP provides quick insights by quickly integrating various data sets from any source and letting the application guide you through data cleaning, discovery, and merging processes.
8. Altair Monarch
A desktop-based self-service data preparation tool called Altair Monarch can connect to a variety of data sources, including unstructured, cloud-based, and big data. No coding is necessary for data connection, cleaning, or modification operations. More than 80 pre-built data preparation functions are included in the tool, and models created with it can be imported into popular BI or other analytics platforms. The browser-based Altair Knowledge Hub offers visual data preparation while also using machine learning to suggest data transformation and enrichment.
9. Collibra
Data intelligence solutions are offered by Collibra. In order to create a data-based culture for the digital enterprise, it provides a cloud-based platform that links IT and the business. It aids in the reduction of complexity, risk, and expense for IT firms. The Free University of Brussels' STARLab was the source of Collibra. All essential data governance and stewardship tasks, such as master data management, data quality, and metadata management, are covered by the Data Governance Center.
10. Incorta
A unified data and analytics platform designed for corporate agility is offered by Incorta. With its cutting-edge technology, the firm receives 100% of the useful data, eliminating the need for conventional data translation and aggregation steps in the process. Data preparation for analysis is made simple by pre-packaged data apps for popular corporate software like Oracle E-Business Suite (EBS), NetSuite, and more.
Data Preparation FAQs
Finding, combining, cleaning, manipulating, and sharing curated datasets for various data and analytics use cases, such as analytics and business intelligence (BI), data science and machine learning (ML), and self-service data integration, is done through the iterative and agile process of data preparation.
Data preprocessing, profiling, cleansing, validation, and transformation are all parts of data preparation. It frequently includes entails combining data from various internal systems and outside sources.
There are two possible sources of data: internal sources and external sources. Primary data refers to information received from internal sources, whereas secondary data refers to information gathered from external sources. All of the data must be gathered through primary or secondary research in order to be analyzed.
