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Lipperhey
Amsterdam, Netherlands
A
1-10 Employees
2009
Key takeaway
Dataprovider.com specializes in transforming the vast and unstructured data of the internet into a structured database, providing actionable insights and data intelligence. Their platform offers unique insights into companies, making it a valuable resource for leveraging big data effectively.
Reference
Product
Technology Recipes | Dataprovider.com
At Dataprovider.com we transform the internet into a structured database of web data. Use our software to gain unique insights into companies.
Datapro MVP Python Specialization
Visakhapatnam, India
D
51-100 Employees
1990
Key takeaway
DATAPRO is a prominent Skill Development Training Centre in India, offering quality training across various locations.
Reference
Service
Datapro |
Datapro
MyDataProvider
Minsk, Belarus
C
1-10 Employees
2009
Key takeaway
MyDataProvider specializes in cloud-based software for web scraping and price monitoring, offering customized data extraction solutions tailored to specific business needs. Their dedicated team ensures efficient management of information, allowing e-commerce companies to focus on their core competencies while accessing the data necessary for informed decision-making.
Reference
Core business
About company | MyDataProvider
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Data Pro Software Solutions
Kyiv, Ukraine
B
1-10 Employees
2012
Key takeaway
Data Pro is an expert in leveraging advanced algorithms and machine learning to unlock sustainable growth for businesses, making it a valuable partner for addressing digital challenges. Their innovative AI solutions streamline processes and deliver transformative outcomes, which can be particularly relevant in the context of big data.
Reference
Service
Services – Data Pro Software Solutions
Delta Data
Columbus, United States
B
101-250 Employees
1985
Key takeaway
Delta Data Distribution Solutions focuses on simplifying the servicing and trading of assets in pooled investment products, enhancing transparency and efficiency in the relationship between asset managers and distributors. Their comprehensive control analysis and in-depth reviews of intermediary audit reports significantly improve compliance and streamline operations.
Reference
Product
Portfolio - DeltaData
Bean Data
Gray, United States
B
1-10 Employees
2015
Key takeaway
Bean Data specializes in providing professional and affordable technology solutions, which may include data services. Their focus on creating a technologically sound work environment and offering support for information technology needs aligns with the interests related to Big Data.
Reference
Service
Data Services | Bean Data
btProvider
Bucharest, Romania
B
11-50 Employees
2012
Key takeaway
btProvider specializes in transforming organizations into data-driven companies by offering consultancy and implementation services in Big Data, Data Analytics, and Business Intelligence. Their expertise includes advanced solutions for data discovery, predictive analytics, and integration, making them a key partner for businesses looking to enhance their digitalization process.
Reference
Core business
btProvider - a Data Analytics & a Digital Transformation Company
btProvider is focused on transforming organizations into data driven companies by offering data analytics services, big data analytics and data integration.
PRODATA
Sandton, South Africa
C
11-50 Employees
1992
Key takeaway
Prodata is a leading Value Added Distributor of specialized hardware and software solutions, making it a preferred partner for businesses seeking innovative products and support. With its extensive product knowledge and strong management, Prodata is well-positioned to address the needs of clients in the evolving landscape of technology.
Reference
Core business
Prodata - Value Added IT Distributor
Dataproof
Birmingham, United Kingdom
A
1-10 Employees
1979
Key takeaway
Dataproof has been providing comprehensive design and printing services since 1979, ensuring high-quality results and fast delivery. As a dedicated print manager, they handle a wide range of printed goods and media for firms nationwide.
Reference
Product
PRODUCTS - Dataproof
DataBP
New York, United States
B
11-50 Employees
2013
Key takeaway
DataBP is a leader in market data commercialization, offering a comprehensive platform and managed services that enable data businesses to efficiently handle the complexities of data sales and operations. Their solutions are designed to drive growth and enhance customer experiences, making data management as seamless as online shopping.
Reference
Product
product Archives - DataBP
Technologies which have been searched by others and may be interesting for you:
A selection of suitable products and services provided by verified companies according to your search.
Product
edbic
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Service
EMCP
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A selection of suitable use cases for products or services provided by verified companies according to your search.
Use case
Continuous monitoring
Manufacturing
The challenge Blickle has always prided itself on the superior quality of its wheels and castors. To further enhance this quality with modern technology, the company decided to migrate its production processes to Industry 4.0 standards. This planned transition should have minimal impact on the three-shift production operation, while maintaining flexibility and openness for future digitalization initiatives. The solution Blickle IT developed a concept to enable a sustainable and gradual transformation. At the heart of the strategy is edbic, which enables condition monitoring. Acting as a central data hub, edbic seamlessly extracts data from the machines, transfers it to the ERP system and provides full production transparency. The result With the implementation of edbic, machine data no longer reaches IT incomplete or delayed. Immediate data analysis enables rapid problem resolution. Automatic punching presses are monitored to determine output results, missing parts, quantities and more. By eliminating most of the Excel lists previously used, edbic has significantly streamlined operations. In polyurethane production, edbic identifies and corrects problems, contributing to Blickle's high quality castors and wheels. In addition, edbic is now being used beyond production, facilitating connections to payment providers in the web shop and establishing a communication link with SAP. Outlook for the future Blickle plans to further refine the system by using machine data comparison for predictive maintenance. In addition, the company is considering implementing the compacer IoT gateway to take communication between machines and the ERP system to a new level of automation.
Use case
IoT gateway and Industry 4.0 application
Industry 4.0, Manufacturing
The challenge: BURKHARDT+WEBER is renowned for its expertise in large machining centres. Headquartered in Reutlingen, Germany, the company has a global presence and supplies its products to customers around the world who place a premium on quality. For 130 years, BURKHARDT+WEBER has focused on developing state-of-the-art production solutions for the demanding machining of steel, cast iron and titanium components. The development of these machining centres is the collaborative work of interdisciplinary teams, and all essential components, as well as in-house developments, are manufactured within the company. The compacer IoT solution, built on the edbic platform, is planned for future integration into BURKHARDT+WEBER machining centres. The installation of the compacer IoT gateway enables data collection from the machine's control system. In the long term, BURKHARDT+WEBER machines will offer a wide range of data that can be examined in real time to provide a detailed overview of the machine's condition and efficiency on a dashboard. The solution: An IoT hub will process the collected data, enabling a variety of assessments and ensuring that the operator is kept informed at all times. With machines connected to the compactor solution, condition monitoring is possible, paving the way for the implementation of predictive maintenance. With this approach, BURKHARDT+WEBER enables its customers to successfully implement upcoming digital transformation projects within their production processes.
Use case
Continuous monitoring
Manufacturing
The challenge Blickle has always prided itself on the superior quality of its wheels and castors. To further enhance this quality with modern technology, the company decided to migrate its production processes to Industry 4.0 standards. This planned transition should have minimal impact on the three-shift production operation, while maintaining flexibility and openness for future digitalization initiatives. The solution Blickle IT developed a concept to enable a sustainable and gradual transformation. At the heart of the strategy is edbic, which enables condition monitoring. Acting as a central data hub, edbic seamlessly extracts data from the machines, transfers it to the ERP system and provides full production transparency. The result With the implementation of edbic, machine data no longer reaches IT incomplete or delayed. Immediate data analysis enables rapid problem resolution. Automatic punching presses are monitored to determine output results, missing parts, quantities and more. By eliminating most of the Excel lists previously used, edbic has significantly streamlined operations. In polyurethane production, edbic identifies and corrects problems, contributing to Blickle's high quality castors and wheels. In addition, edbic is now being used beyond production, facilitating connections to payment providers in the web shop and establishing a communication link with SAP. Outlook for the future Blickle plans to further refine the system by using machine data comparison for predictive maintenance. In addition, the company is considering implementing the compacer IoT gateway to take communication between machines and the ERP system to a new level of automation.
Big Data refers to the vast volumes of structured and unstructured data generated from various sources, including social media, sensors, transactions, and more. This data is characterized by its high volume, velocity, and variety, making it challenging to process using traditional data management tools. Organizations leverage Big Data technologies to analyze and extract valuable insights, enabling informed decision-making, improving operational efficiency, and enhancing customer experiences. By utilizing advanced analytics, machine learning, and cloud computing, businesses can harness the power of Big Data to gain a competitive edge in their respective industries.
Big Data plays a crucial role in enhancing decision-making processes across various industries. By analyzing vast amounts of data, organizations can uncover patterns and trends that inform strategic choices. This data-driven approach allows businesses to make informed predictions about customer behavior, market trends, and operational efficiency. Furthermore, utilizing Big Data enables companies to identify opportunities for improvement and innovation. With real-time analytics, decision-makers can respond swiftly to changing conditions, ensuring they remain competitive in an ever-evolving marketplace. Overall, the integration of Big Data into decision-making fosters a more proactive and evidence-based strategy.
The main components of Big Data architecture include data sources, storage solutions, processing frameworks, and analytics tools.
1. Data Sources
These are the origins of data, which can include structured, semi-structured, and unstructured data from various sources like social media, IoT devices, and enterprise applications.
2. Storage Solutions
Big Data requires scalable storage solutions, such as distributed file systems and cloud storage, to accommodate vast amounts of data efficiently.
3. Processing Frameworks
Processing frameworks like Hadoop and Spark are essential for managing and analyzing large datasets. They enable parallel processing, which enhances performance and speed.
4. Analytics Tools
These tools provide insights through data analysis, visualization, and reporting. They help organizations make data-driven decisions based on the patterns and trends identified in the data.
Big Data analytics significantly differs from traditional analytics in its ability to process large volumes of diverse data types in real-time. Traditional analytics often relies on structured data from relational databases, making it limited in scope and speed. In contrast, Big Data analytics utilizes advanced technologies and frameworks, such as Hadoop and Spark, to analyze unstructured and semi-structured data from various sources, including social media, IoT devices, and more. Moreover, the scale and speed at which Big Data analytics operate allow organizations to derive insights from massive datasets quickly. This capability enables businesses to make data-driven decisions faster, offering a competitive edge in rapidly changing markets. The integration of machine learning and artificial intelligence in Big Data analytics further enhances its predictive abilities, providing deeper insights compared to conventional methods.
Implementing Big Data solutions presents several challenges that organizations must navigate effectively. One significant issue is data integration, where disparate data sources may have varying formats and structures, complicating the consolidation process. Additionally, ensuring data quality is critical; poor-quality data can lead to inaccurate analyses and misleading insights. Another challenge lies in scalability. As data volumes grow, organizations must ensure their infrastructure can handle increased loads without sacrificing performance. Moreover, there are concerns regarding data security and privacy, especially with strict regulations in place. Organizations need robust frameworks to protect sensitive information while complying with legal requirements. Finally, the shortage of skilled professionals in Big Data analytics can hinder effective implementation, as businesses struggle to find qualified talent to manage and interpret data effectively.
Some interesting numbers and facts about your company results for Big Data
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 4424 |
| Amount of suitable service providers | 4304 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 1979 |
| Youngest suiting company | 2015 |
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Some interesting questions that has been asked about the results you have just received for Big Data
What are related technologies to Big Data?
Based on our calculations related technologies to Big Data are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce
Which industries are mostly working on Big Data?
The most represented industries which are working in Big Data are IT, Software and Services, Other, Marketing Services, Consulting, Finance and Insurance
How does ensun find these Big Data Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
