Data Cleaning Tools Market Outlook

As of 2023, the global market size for data cleaning tools is estimated at $2.5 billion, with projections indicating that it will reach approximately $7.1 billion by 2032, reflecting a robust CAGR of 12.1% during the forecast period. This growth is primarily driven by the increasing importance of data quality in business intelligence and analytics workflows across various industries.

The growth of the data cleaning tools market can be attributed to several critical factors. Firstly, the exponential increase in data generation across industries necessitates efficient tools to manage data quality. Poor data quality can result in significant financial losses, inefficient business processes, and faulty decision-making. Organizations recognize the value of clean, accurate data in driving business insights and operational efficiency, thereby propelling the adoption of data cleaning tools. Additionally, regulatory requirements and compliance standards also push companies to maintain high data quality standards, further driving market growth.

Another significant growth factor is the rising adoption of AI and machine learning technologies. These advanced technologies rely heavily on high-quality data to deliver accurate results. Data cleaning tools play a crucial role in preparing datasets for AI and machine learning models, ensuring that the data is free from errors, inconsistencies, and redundancies. This surge in the use of AI and machine learning across various sectors like healthcare, finance, and retail is driving the demand for efficient data cleaning solutions.

The proliferation of big data analytics is another critical factor contributing to market growth. Big data analytics enables organizations to uncover hidden patterns, correlations, and insights from large datasets. However, the effectiveness of big data analytics is contingent upon the quality of the data being analyzed. Data cleaning tools help in sanitizing large datasets, making them suitable for analysis and thus enhancing the accuracy and reliability of analytics outcomes. This trend is expected to continue, fueling the demand for data cleaning tools.

In terms of regional growth, North America holds a dominant position in the data cleaning tools market. The region's strong technological infrastructure, coupled with the presence of major market players and a high adoption rate of advanced data management solutions, contributes to its leadership. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period. The rapid digitization of businesses, increasing investments in IT infrastructure, and a growing focus on data-driven decision-making are key factors driving the market in this region.

As organizations strive to maintain high data quality standards, the role of an Email List Cleaning Service becomes increasingly vital. These services ensure that email databases are free from invalid addresses, duplicates, and outdated information, thereby enhancing the effectiveness of marketing campaigns and communications. By leveraging sophisticated algorithms and validation techniques, email list cleaning services help businesses improve their email deliverability rates and reduce the risk of being flagged as spam. This not only optimizes marketing efforts but also protects the reputation of the sender. As a result, the demand for such services is expected to grow alongside the broader data cleaning tools market, as companies recognize the importance of maintaining clean and accurate contact lists.

Component Analysis

The data cleaning tools market can be segmented by component into software and services. The software segment encompasses various tools and platforms designed for data cleaning, while the services segment includes consultancy, implementation, and maintenance services provided by vendors.

The software segment holds the largest market share and is expected to continue leading during the forecast period. This dominance can be attributed to the increasing adoption of automated data cleaning solutions that offer high efficiency and accuracy. These software solutions are equipped with advanced algorithms and functionalities that can handle large volumes of data, identify errors, and correct them without manual intervention. The rising adoption of cloud-based data cleaning software further bolsters this segment, as it offers scalability and ease of

At Thomson Data, we help businesses clean up and manage messy B2B databases to ensure they are up-to-date, correct, and detailed. We believe your sales development representatives and marketing representatives should focus on building meaningful relationships with prospects, not scrubbing through bad data.

Here are the key steps involved in our B2B data cleansing process:

1. Data Auditing: We begin with a thorough audit of the database to identify errors, gaps, and inconsistencies, which majorly revolve around identifying outdated, incomplete, and duplicate information.

2. Data Standardization: Ensuring consistency in the data records is one of our prime services; it includes standardizing job titles, addresses, and company names. It ensures that they can be easily shared and used by different teams.

3. Data Deduplication: Another way we improve efficiency is by removing all duplicate records. Data deduplication is important in a large B2B dataset as multiple records from the same company may exist in the database.

4. Data Enrichment: After the first three steps, we enrich your data, fill in the missing details, and then enhance the database with up-to-date records. This is the step that ensures the database is valuable, providing insights that are actionable and complete.

What are the Key Benefits of Keeping the Data Clean with Thomson Data’s B2B Data Cleansing Service? Once you understand the benefits of our data cleansing service, it will entice you to optimize your data management practices, and it will additionally help you stay competitive in today’s data-driven market.

Here are some advantages of maintaining a clean database with Thomson Data:

1. Better ROI for your Sales and Marketing Campaigns: Our clean data will magnify your precise targeting, enabling you to strategize for effective campaigns, increased conversion rate, and ROI.

2. Compliant with Data Regulations:
   The B2B data cleansing services we provide are compliant to global data norms.

3. Streamline Operations: Your efforts are directed in the right channel when your data is clean and accurate, as your team doesn’t have to spend their valuable time fixing errors.

To summarize, we would again bring your attention to how accurate data is essential for driving sales and marketing in a B2B environment. It enhances your business prowess in the avenues of decision-making and customer relationships. Therefore, it is better to have a proactive approach toward B2B data cleansing service and outsource our offerings to stay competitive by unlocking the full potential of your data.

Send us a request and we will be happy to assist you.

Embark on a transformative journey with our Data Cleaning Project, where we meticulously refine and polish raw data into valuable insights. Our project focuses on streamlining data sets, removing inconsistencies, and ensuring accuracy to unlock its full potential.

Through advanced techniques and rigorous processes, we standardize formats, address missing values, and eliminate duplicates, creating a clean and reliable foundation for analysis. By enhancing data quality, we empower organizations to make informed decisions, drive innovation, and achieve strategic objectives with confidence.

Join us as we embark on this essential phase of data preparation, paving the way for more accurate and actionable insights that fuel success."

Data Cleansing Software Market Outlook

The global data cleansing software market size was valued at approximately USD 1.5 billion in 2023 and is projected to reach around USD 4.2 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 12.5% during the forecast period. This substantial growth can be attributed to the increasing importance of maintaining clean and reliable data for business intelligence and analytics, which are driving the adoption of data cleansing solutions across various industries.

The proliferation of big data and the growing emphasis on data-driven decision-making are significant growth factors for the data cleansing software market. As organizations collect vast amounts of data from multiple sources, ensuring that this data is accurate, consistent, and complete becomes critical for deriving actionable insights. Data cleansing software helps organizations eliminate inaccuracies, inconsistencies, and redundancies, thereby enhancing the quality of their data and improving overall operational efficiency. Additionally, the rising adoption of advanced analytics and artificial intelligence (AI) technologies further fuels the demand for data cleansing software, as clean data is essential for the accuracy and reliability of these technologies.

Another key driver of market growth is the increasing regulatory pressure for data compliance and governance. Governments and regulatory bodies across the globe are implementing stringent data protection regulations, such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States. These regulations mandate organizations to ensure the accuracy and security of the personal data they handle. Data cleansing software assists organizations in complying with these regulations by identifying and rectifying inaccuracies in their data repositories, thus minimizing the risk of non-compliance and hefty penalties.

The growing trend of digital transformation across various industries also contributes to the expanding data cleansing software market. As businesses transition to digital platforms, they generate and accumulate enormous volumes of data. To derive meaningful insights and maintain a competitive edge, it is imperative for organizations to maintain high-quality data. Data cleansing software plays a pivotal role in this process by enabling organizations to streamline their data management practices and ensure the integrity of their data. Furthermore, the increasing adoption of cloud-based solutions provides additional impetus to the market, as cloud platforms facilitate seamless integration and scalability of data cleansing tools.

Regionally, North America holds a dominant position in the data cleansing software market, driven by the presence of numerous technology giants and the rapid adoption of advanced data management solutions. The region is expected to continue its dominance during the forecast period, supported by the strong emphasis on data quality and compliance. Europe is also a significant market, with countries like Germany, the UK, and France showing substantial demand for data cleansing solutions. The Asia Pacific region is poised for significant growth, fueled by the increasing digitalization of businesses and the rising awareness of data quality's importance. Emerging economies in Latin America and the Middle East & Africa are also expected to witness steady growth, driven by the growing adoption of data-driven technologies.

The role of Data Quality Tools cannot be overstated in the context of data cleansing software. These tools are integral in ensuring that the data being processed is not only clean but also of high quality, which is crucial for accurate analytics and decision-making. Data Quality Tools help in profiling, monitoring, and cleansing data, thereby ensuring that organizations can trust their data for strategic decisions. As organizations increasingly rely on data-driven insights, the demand for robust Data Quality Tools is expected to rise. These tools offer functionalities such as data validation, standardization, and enrichment, which are essential for maintaining the integrity of data across various platforms and applications. The integration of these tools with data cleansing software enhances the overall data management capabilities of organizations, enabling them to achieve greater operational efficiency and compliance with data regulations.

Component Analysis

The data cle

Sample data for exercises in Further Adventures in Data Cleaning.

Learn more about Market Research Intellect's Data Cleansing Software Market Report, valued at USD 2.5 billion in 2024, and set to grow to USD 5.1 billion by 2033 with a CAGR of 9.2% (2026-2033).

A messy data for demonstrating "how to clean data using spreadsheet". This dataset was intentionally formatted to be messy, for the purpose of demonstration. It was collated from here - https://openafrica.net/dataset/historic-and-projected-rainfall-and-runoff-for-4-lake-victoria-sub-regions

What is Account-Based-Marketing? Account-based marketing, or ABM, is a business strategy that focuses your resources on a specific segment of customer accounts. It's all about understanding your customers on a personal level and delivering personalized campaigns that resonate with their needs and preferences.

Why should you use Thomson Data’s Data solution for Account Based Marketing (ABM)? Utilizing Account-based marketing data for your marketing campaign might seem like a long-draw-out approach, but it is absolutely worth the hassle.

Here are some of the benefits you will definitely be interested in.

Boost Lead Generation: Our database is designed for effective account-based marketing that will boost lead generation. We enable you to target specific accounts, and our data insights will help you tailor the messages according to their needs and pain points.

Retain Email Subscribers: Retaining your subscribers is also a concerning challenge. Using our database for account-based marketing will help you to connect with your clients on a personal level. Enabling you to keep them engaged will encourage these clients to consider your products and services whenever they need one.

Increases profits: As Thomson Data’s records heighten the tone for personalization, you can connect with your prospective clientele on a personal level. When you do it in the right way, it is significantly reflected in your sales figures.

Gain Insights: Get 100+ insights from our data to make better decision making and implement in your Account based marketing strategies.

Our ABM data can be used for improving your conversions by 3x times.

Our Account based marketing data can be used by: 1. B2b companies 2. Sales Teams 3. Marketing Teams 4. C- suite Executives 5. Agencies and Service providers 6. Enterprise Level Organizations and more.

Thomson Data is perfect for ABM and will certainly help you run campaigns that target customer acquisition as well as customer retention. We provide you an access to the complete data solution to help you connect and impress your target audience.

Send us a request to know more details about our Account based marketing data and we will be happy to assist you.

The data cleansing tools market is experiencing robust growth, driven by the escalating volume and complexity of data across various sectors. The increasing need for accurate and reliable data for decision-making, coupled with stringent data privacy regulations (like GDPR and CCPA), fuels demand for sophisticated data cleansing solutions. Businesses, regardless of size, are recognizing the critical role of data quality in enhancing operational efficiency, improving customer experiences, and gaining a competitive edge. The market is segmented by application (agencies, large enterprises, SMEs, personal use), deployment type (cloud, SaaS, web, installed, API integration), and geography, reflecting the diverse needs and technological preferences of users. While the cloud and SaaS models are witnessing rapid adoption due to scalability and cost-effectiveness, on-premise solutions remain relevant for organizations with stringent security requirements. The historical period (2019-2024) showed substantial growth, and this trajectory is projected to continue throughout the forecast period (2025-2033). Specific growth rates will depend on technological advancements, economic conditions, and regulatory changes. Competition is fierce, with established players like IBM, SAS, and SAP alongside innovative startups continuously improving their offerings. The market's future depends on factors such as the evolution of AI and machine learning capabilities within data cleansing tools, the increasing demand for automated solutions, and the ongoing need to address emerging data privacy challenges. The projected Compound Annual Growth Rate (CAGR) suggests a healthy expansion of the market. While precise figures are not provided, a realistic estimate based on industry trends places the market size at approximately $15 billion in 2025. This is based on a combination of existing market reports and understanding of the growth of related fields (such as data analytics and business intelligence). This substantial market value is further segmented across the specified geographic regions. North America and Europe currently dominate, but the Asia-Pacific region is expected to exhibit significant growth potential driven by increasing digitalization and adoption of data-driven strategies. The restraints on market growth largely involve challenges related to data integration complexity, cost of implementation for smaller businesses, and the skills gap in data management expertise. However, these are being countered by the emergence of user-friendly tools and increased investment in data literacy training.

Dataset

This dataset was created by AbdElRahman16

Contents

Materials from workshop conducted for Monroe Library faculty as part of TLT/Faculty Development/Digital Scholarship on 2018-04-05. Objectives:Clean dataAnalyze data using pivot tablesVisualize dataDesign accessible instruction for working with dataAssociated Research Guide at http://researchguides.loyno.edu/data_workshopData sets are from the following:

BaroqueArt Dataset by CulturePlex Lab is licensed under CC0 What's on the Menu? Menus by New York Public Library is licensed under CC0 Dog movie stars and dog breed popularity by Ghirlanda S, Acerbi A, Herzog H is licensed under CC BY 4.0 NOPD Misconduct Complaints, 2016-2018 by City of New Orleans Open Data is licensed under CC0 U.S. Consumer Product Safety Commission Recall Violations by CU.S. Consumer Product Safety Commission, Violations is licensed under CC0 NCHS - Leading Causes of Death: United States by Data.gov is licensed under CC0 Bob Ross Elements by Episode by Walt Hickey, FiveThirtyEight, is licensed under CC BY 4.0 Pacific Walrus Coastal Haulout 1852-2016 by U.S. Geological Survey, Alaska Science Center is licensed under CC0 Australia Registered Animals by Sunshine Coast Council is licensed under CC0

Computer Junk Cleanup Software Market Outlook

The global market size for computer junk cleanup software was valued at approximately USD 2.4 billion in 2023 and is projected to reach around USD 4.9 billion by 2032, growing at a CAGR of 7.8% during the forecast period. The growth of this market is fueled by increasing digitalization and the expansion of IT infrastructures across various industries, necessitating efficient management of system performance and storage solutions.

One of the primary growth factors for this market is the exponential increase in data generation, which leads to the accumulation of redundant and obsolete files that clutter computer systems. With the rise of big data and the Internet of Things (IoT), organizations are grappling with vast amounts of data, making it essential to employ computer junk cleanup software to optimize system performance and storage. Additionally, the rapid technological advancements in AI and machine learning have enabled more efficient and effective junk cleanup solutions, which further drive market growth.

Another significant factor contributing to market growth is the increasing awareness among individual users and enterprises about the importance of maintaining optimal system performance. As computers and other digital devices are integral to daily operations, both at work and home, ensuring their efficient functioning becomes crucial. Regular use of junk cleanup software helps in enhancing system speed, extending hardware lifespan, and preventing potential security vulnerabilities caused by unnecessary files and software. This awareness is pushing the adoption rate higher across various user segments.

Moreover, the growing trend of remote work and the proliferation of advanced digital devices have made it imperative for organizations to deploy junk cleanup software to maintain system efficiency and security. The shift towards a remote working model necessitates advanced software solutions for performance management and data security, further bolstering the market demand for computer junk cleanup software. Companies are increasingly investing in these solutions to ensure seamless operations, which is amplifying market growth.

In the realm of digital management, Data Cleansing Software plays a pivotal role in ensuring that systems remain efficient and free from unnecessary clutter. As organizations accumulate vast amounts of data, the need for tools that can effectively clean and organize this data becomes paramount. Data Cleansing Software helps in identifying and rectifying errors, removing duplicate entries, and ensuring that the data remains accurate and up-to-date. This not only enhances the performance of computer systems but also supports better decision-making processes by providing clean and reliable data. The integration of such software with junk cleanup solutions can significantly optimize system performance, making it an essential component for enterprises aiming to maintain high standards of data integrity.

From a regional perspective, North America is expected to dominate the computer junk cleanup software market, owing to the high digital literacy rate, robust IT infrastructure, and significant adoption of advanced technologies. However, regions such as Asia Pacific are also witnessing rapid market growth due to the increasing number of small and medium enterprises (SMEs), rising internet penetration, and growing awareness about system optimization and security. Europe follows closely with substantial investments in IT solutions and digital transformation initiatives.

Component Analysis

The computer junk cleanup software market is segmented into software and services. The software segment encompasses standalone applications and integrated system optimization tools that users can install on their devices. This segment is the largest contributor to market revenue, driven by widespread adoption among individual users and enterprises seeking to enhance system performance. These software solutions often come with features such as real-time monitoring, automated cleanup, and advanced algorithms capable of identifying and removing redundant files without compromising essential data.

The services segment, on the other hand, includes professional services, such as system audits, consultancy, installation, and maintenance offered by vendors. This segment is witnessing growth as enterprises increasingly lean on expert services for comprehen

Ahoy, data enthusiasts! Join us for a hands-on workshop where you will hoist your sails and navigate through the Statistics Canada website, uncovering hidden treasures in the form of data tables. With the wind at your back, you’ll master the art of downloading these invaluable Stats Can datasets while braving the occasional squall of data cleaning challenges using Excel with your trusty captains Vivek and Lucia at the helm.

DomainIQ is a comprehensive global Domain Name dataset for organizations that want to build cyber security, data cleaning and email marketing applications. The dataset consists of the DNS records for over 267 million domains, updated daily, representing more than 90% of all public domains in the world.

The data is enriched by over thirty unique data points, including identifying the mailbox provider for each domain and using AI based predictive analytics to identify elevated risk domains from both a cyber security and email sending reputation perspective.

DomainIQ from Datazag offers layered intelligence through a highly flexible API and as a dataset, available for both cloud and on-premises applications. Standard formats include CSV, JSON, Parquet, and DuckDB.

Custom options are available for any other file or database format. With daily updates and constant research from Datazag, organizations can develop their own market leading cyber security, data cleaning and email marketing applications supported by comprehensive and accurate data from Datazag. Data updates available on a daily, weekly and monthly basis. API data is updated on a daily basis.

This clean dataset is a refined version of our company datasets, consisting of 35M+ data records.

It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B data. After cleaning, this data is also enriched by leveraging a carefully instructed large language model (LLM).

AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

Coresignal is a leading public business data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

The MRO (Maintenance, Repair, and Operations) Data Cleansing and Enrichment Service market is experiencing robust growth, driven by the increasing need for accurate and reliable data across various industries. The digital transformation sweeping manufacturing, oil & gas, and transportation sectors is creating a surge in data volume, but much of this data is fragmented, incomplete, or inconsistent. This necessitates sophisticated data cleansing and enrichment solutions to improve operational efficiency, predictive maintenance capabilities, and informed decision-making. The market's expansion is fueled by the adoption of Industry 4.0 technologies, including IoT sensors and connected devices, generating massive datasets requiring rigorous cleaning and enrichment processes. Furthermore, regulatory compliance pressures and the need for improved supply chain visibility are contributing to strong market demand. We estimate the 2025 market size to be $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 15% projected through 2033. This growth is primarily driven by the Chemical, Oil & Gas, and Pharmaceutical industries' increasing reliance on data-driven insights for optimizing operations and reducing downtime. Significant regional variations exist, with North America and Europe currently holding the largest market shares, but rapid growth is anticipated in the Asia-Pacific region due to the increasing industrialization and digitalization initiatives underway. The market segmentation by application reveals a diverse landscape. The Chemical and Oil & Gas industries are early adopters, followed closely by Pharmaceuticals, leveraging data cleansing and enrichment to improve safety, comply with regulations, and optimize asset management. The Mining and Transportation sectors are also rapidly adopting these services to enhance operational efficiency and predictive maintenance. Within the types of services offered, data cleansing represents a larger share currently, focusing on identifying and removing inconsistencies and inaccuracies. However, data enrichment, which involves augmenting existing data with external sources to improve its completeness and context, is experiencing accelerated growth due to its capacity to unlock deeper insights. While several established players operate in the market, such as Enventure, Sphera, and OptimizeMRO, the landscape is also characterized by numerous smaller, specialized service providers, indicative of a competitive and dynamic market structure. The presence of regional players further suggests opportunities for both consolidation and expansion in the coming years.

We offer comprehensive data collection services that cater to a wide range of industries and applications. Whether you require image, audio, or text data, we have the expertise and resources to collect and deliver high-quality data that meets your specific requirements. Our data collection methods include manual collection, web scraping, and other automated techniques that ensure accuracy and completeness of data.

Our team of experienced data collectors and quality assurance professionals ensure that the data is collected and processed according to the highest standards of quality. We also take great care to ensure that the data we collect is relevant and applicable to your use case. This means that you can rely on us to provide you with clean and useful data that can be used to train machine learning models, improve business processes, or conduct research.

We are committed to delivering data in the format that you require. Whether you need raw data or a processed dataset, we can deliver the data in your preferred format, including CSV, JSON, or XML. We understand that every project is unique, and we work closely with our clients to ensure that we deliver the data that meets their specific needs. So if you need reliable data collection services for your next project, look no further than us.

OpenRefine (formerly Google Refine) is a powerful free and open source tool for data cleaning, enabling you to correct errors in the data, and make sure that the values and formatting are consistent. In addition, OpenRefine records your processing steps, enabling you to apply the same cleaning procedure to other data, and enhancing the reproducibility of your analysis. This workshop will teach you to use OpenRefine to clean and format data and automatically track any changes that you make.

This dataset presents a dual-version representation of employment-related data from India, crafted to highlight the importance of data cleaning and transformation in any real-world data science or analytics project.

🔹 Dataset Composition:

It includes two parallel datasets: 1. Messy Dataset (Raw) – Represents a typical unprocessed dataset often encountered in data collection from surveys, databases, or manual entries. 2. Cleaned Dataset – This version demonstrates how proper data preprocessing can significantly enhance the quality and usability of data for analytical and visualization purposes.

Each record captures multiple attributes related to individuals in the Indian job market, including: - Age Group
- Employment Status (Employed/Unemployed)
- Monthly Salary (INR)
- Education Level
- Industry Sector
- Years of Experience
- Location
- Perceived AI Risk
- Date of Data Recording

Transformations & Cleaning Applied:

The raw dataset underwent comprehensive transformations to convert it into its clean, analysis-ready form: - Missing Values: Identified and handled using either row elimination (where critical data was missing) or imputation techniques. - Duplicate Records: Identified using row comparison and removed to prevent analytical skew. - Inconsistent Formatting: Unified inconsistent naming in columns (like 'monthly_salary_(inr)' → 'Monthly Salary (INR)'), capitalization, and string spacing. - Incorrect Data Types: Converted columns like salary from string/object to float for numerical analysis. - Outliers: Detected and handled based on domain logic and distribution analysis. - Categorization: Converted numeric ages into grouped age categories for comparative analysis. - Standardization: Uniform labels for employment status, industry names, education, and AI risk levels were applied for visualization clarity.

Purpose & Utility:

This dataset is ideal for learners and professionals who want to understand: - The impact of messy data on visualization and insights - How transformation steps can dramatically improve data interpretation - Practical examples of preprocessing techniques before feeding into ML models or BI tools

It's also useful for: - Training ML models with clean inputs
- Data storytelling with visual clarity
- Demonstrating reproducibility in data cleaning pipelines

By examining both the messy and clean datasets, users gain a deeper appreciation for why “garbage in, garbage out” rings true in the world of data science.

The Data Cleansing Tools market is rapidly evolving as businesses increasingly recognize the importance of data quality in driving decision-making and strategic initiatives. Data cleansing, also known as data scrubbing or data cleaning, involves the process of identifying and correcting errors and inconsistencies in