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Identify valuable information with Data Science

Extract hidden, valuable information from Big Data with Data Science to make data-driven decisions in the future.Contakt us now
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Artificial Intelligence (AI) - but only with lane departure warning systemTransparency and traceability of AI is the biggest challenge for using AI. Read our blog post on the topic of AI (German).Read in German

What is Data Science?

Data Science has for some time been considered the supreme discipline in the discovery of valuable information in larger data sets. It promises to extract hidden, valuable information from data of any structure – i.e. not only numerical values such as measured values and key figures, which are often referred to as "structured", but also texts, images, videos and even sounds ("unstructured data"). 

  • Hidden, because this information is very difficult/long to reveal or, due to the limited capacity of the human brain, cannot be revealed by just looking at it.
  • Valuable, because information may be hidden, but knowledge of it could add value or lead to action to achieve a desired effect.

Learn all about the benefits of using it, the different disciplines that make up Data Science, and the factors that play a role. Together we will find the optimal way to find valuable information in your data with Data Science. We will be happy to advise you.

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4 reasons for using Data Science

Reap the benefits of using Data Science:

Recognize data potential

Every company has vast amounts of data. Through Data Science and the respective processes, the potential of insights from this data becomes visible

Data-Driven Enterprise

Linking enterprise data, automated analytical processing, supported by Artificial Intelligence, enables the "data-driven enterprise"

Reliability & Transparency

In every Data Science project, data quality and data origin become visible – the prerequisite for comprehensible, transparent decisions

New business models

The consistent use of all the company's data not only enables existing processes to be improved, but also creates the basis for complete new business models

Disciplines of Data Science

Here you learn about the different disciplines according to which the necessary data was extracted from the previous systems and prepared for the analytical use case:

 

Artificial Intelligence

Today, the term "Artificial Intelligence" (AI) is often used as an umbrella term for systems that emulate or simulate human thinking. Technologies such as Machine Learning (ML) or Deep Learning with special algorithms play a special role here.

In the context of Data Science, AI is often mentioned when decision support systems are developed for specific use cases. As can be seen on the left chart, Data Science does not exclusively cover the creation of AI, but rather the combination of AI, computer science and expertise. Informatics includes, among other things, obtaining the data, and putting it with the necessary expertise ("domain knowledge") into a format necessary for the AI.

Machine Learning

In Machine Learning, "experiences", i.e. already known results, are processed in a structured manner and a system learns the relationships between input and output variables.

Using a test data set with likewise known results, the learning result (= the recognized mathematical model) is checked and, if necessary, sharpened. Subsequently, the model can be applied to unknown data and predict a result with a certain quality.

Deep Learning

Deep Learning is a sub-discipline of Machine Learning in which neural networks are used. In most cases, large amounts of data are processed without human intervention during the actual learning process (see also Supervised vs. Unsupervised Learning).

Neural networks imitate the functioning of the human brain: they make decisions, question them and, if necessary, learn again. Large neural networks require enormous computing power, which is often provided by GPUs because they are internally capable of performing matrix calculations very quickly. Deep Learning is often used for automatic image or speech recognition.

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Operationalization of Data Science (MLOps)

Data and Artificial Intelligence (AI) can support almost any business process based on facts. Many companies are in the middle of a phase of professional assessment of the algorithms and technical testing of the corresponding technologies. MLOps describes the integration into the business process to exploit the full added value of each algorithm.

More on MLOps

Factors that play a role in Data Science:

  • Stock of data

    The amount of data available has grown enormously. In production, sensors send thousands of measurements per second; in logistics, goods can be tracked by GPS; and when surfing the web, potential buyers consciously or unconsciously leave traces that can be used to draw conclusions about their shopping behavior. 

  • Availability of powerful computing capacity

    It has never been easier or cheaper to process the data supply with mathematical methods. Performance on demand (including in the Cloud) allows capacities to be increased even at short notice, so that in total many use cases become economical more quickly. In addition, there are new parallel computer architectures (including GPUs) that can recognize unexpected combinations and patterns through native processing of mathematical models. 

  • New mathematical methods

    New versions of well-known methods (see parallel processing and GPU), new methods that are rapidly being shared worldwide due to the prevailing "sharing economy", or Artificial Intelligence or Machine Learning methods, make it much easier to model and solve solutions today. 

  • Quality and traceability of the data

    And despite or because of the outstanding possibilities, it is also true for Data Science that the preparation of data from different sources is time-consuming and error-prone. At the same time, the requirements for quality and traceability of the data are increasing in order to substantiate findings or to be able to justify them retrospectively. 

Our services in Data Science:

The combination of requirements and challenges results in a decision matrix for the use of Data Science, AI or ML in the company. Together, we find the right way to make optimal use of the information.

Expertise

With our experts we cover all necessary qualifications for successful Data Science projects. No matter if the connection of data sources, the preparation, assessment, modeling, quantification or operationalization.

Workshops

Together, we identify Data Science potential and discuss the approaches that are valuable for your company and their feasibility. We then determine the best technology for this, in order to then use the insights gained for your business processes.
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The right vendor for every project

Our experts rely on various Open Source tools such as R, Python, Jupyter, but also on commercial tools and solutions from IBM and Microsoft for the implementation of Data Science projects.

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IBM

IBM offers its customers a comprehensive portfolio of solutions and services under the "Watson" brand. IBM differentiates between solutions that comprehensively support the development and operation of AI solutions, predefined AI applications for the analysis of large data volumes, AI APIs for embedding in applications, and ready-made, AI-supported industry solutions. With the "Cloud Pak for Data" IBM provides a technical platform for the operation of the above solutions, supplemented by data integration, data governance, databases and analysis tools.

Microsoft

Microsoft has invested heavily in AI over the past few years, especially in its Azure platform, and offers a robust, comprehensive framework for developing AI solutions in many areas. Ready-to-use services, dedicated infrastructure and tools provide extensive functionality and massively facilitate the deployment of AI applications.

Contact us now!

We would be happy to advise you in a non-binding meeting and show you how you can benefit from Data Science. Just leave your contact details and we will get back to you as soon as possible.

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Dashboards & Reports

The discipline of Business Intelligence provides the necessary means for accessing data. In addition, various methods have developed that help to transport information to the end user through various technologies.

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Business Intelligence

Business Intelligence (BI) is a technology-driven process for analyzing data and presenting usable information. On this basis, sound decisions can be made.

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Conception of individual Analytics and Big Data solutions

We determine the best approach to develop an individual solution from the professional, role-specific requirements – suitable for the respective situation!

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Data Integration, ETL and Data Virtualization

While the term "ETL" (Extract - Transform - Load / or ELT) usually described the classic batch-driven process, today the term "Data Integration" extends to all methods of integration: whether batch, real-time, inside or outside a database, or between any systems.

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Big Data, Data Lake & Data Warehousing

For the optimal solution – with special consideration of the business requirements – we combine different functionalities.

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Data Governance

Data Governance describes all processes that aim to ensure the traceability, quality and protection of data. The need for documentation and traceability increases exponentially as more and more data from different sources is used for decision-making and as a result of the technical possibilities of integration in Data Warehouses or Data Lakes.

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Operationalization of Data Science (MLOps)

Data and Artificial Intelligence (AI) can support almost any business process based on facts. Many companies are in the phase of professional assessment of the algorithms and technical testing of the respective technologies.

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Demand Planning, Forecasting and Optimization

After the data has been prepared and visualized via dashboards and reports, the task is now to use the data obtained accordingly. Digital planning, forecasting and optimization describes all the capabilities of an IT-supported solution in the company to support users in digital analysis and planning.

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Decision Optimization

Mathematical algorithms enable fast and efficient improvement of partially contradictory specifications. As an integral part of the IBM Data Science platform "Cloud Pak for Data" or "IBM Watson Studio", decision optimisation has been decisively expanded and embedded in the Data Science process.

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Jira Service Management from Atlassian

Enable developers, operators, and other teams from different departments to collaborate and improve their service management responsiveness. Respond quickly to incidents, requests, and changes, and provide your customers with an optimized service experience.

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Confluence from Atlassian

Create, organize, and collaborate on tasks - all in a single place. Confluence is a workspace for teams and organizations where you can store your documentation and collaboratively develop and share knowledge. Dynamic pages give your team a place to create, capture, and collaborate around projects or idea development.

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IBM Watson Studio

IBM Watson Studio is an integrated solution for implementing a data science landscape. It helps companies to structure and simplify the process from exploratory analysis to the implementation and operationalisation of the analysis processes.

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IBM SPSS Modeler

IBM SPSS Modeler is a tool that can be used to model and execute tasks, for example in the field of Data Science and Data Mining, via a graphical user interface.

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Incident communication management

Statuspage allows you to keep track of the status of individual system-relevant components as well as a history of past incidents. Our self-created solution also allows you to connect various monitoring tools and query them in specific cycles. The component failure automatically generates an e-mail to your ticket system.

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FinOps Consulting

We advise you both commercially and technically on how to gain transparency over your cloud costs and how to reduce them sustainably.

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FinOps

Gain visibility into your cloud costs and sustainably reduce them by applying best practices from FinOps.

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Anwendungsmöglichkeiten

Learn how you can integrate Atlassian products into your daily business to make your processes more efficient.

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FinOps Microsoft - Microsoft Cloud Cost Optimization

TIMETOACT offers license management and compliance consulting in the Microsoft area, as well as technical consulting (e.g. on the use of Azure Services).

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Cloud from Atlassian

Atlassian Cloud gives even small teams the ability to leverage the Atlassian product world. It allows you to flexibly adjust the number of users. Furthermore, you can choose from three paid variants of Cloud products. In this way, you always adapt your Atlassian product to your individual requirements. The multiple certified Atlassian Cloud solutions are hosted at Amazon Web Services Inc.

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Enterprise Content Management (ECM) & Archiving

With Enterprise Content Management (ECM), all data, information and documents are stored, archived and managed in a context-related manner on a single platform. ECM systems offer numerous advantages for managing the increasing number of (un)structured electronic documents and data.

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Enterprise Content Management (ECM) & Archiving

With Enterprise Content Management (ECM), all data, information and documents are stored, archived and managed in a context-related manner on a single platform. ECM systems offer numerous advantages for managing the increasing number of (un)structured electronic documents and data.

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Enterprise Content Management (ECM) & Archiving

With Enterprise Content Management (ECM), all data, information and documents are stored, archived and managed in a context-related manner on a single platform. ECM systems offer numerous advantages for managing the increasing number of (un)structured electronic documents and data.

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Enterprise Content Management (ECM) & Archiving

With Enterprise Content Management (ECM), all data, information and documents are stored, archived and managed in a context-related manner on a single platform. ECM systems offer numerous advantages for managing the increasing number of (un)structured electronic documents and data.

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IBM Planning Analytics mit Watson

IBM Planning Analytics with Watsons enables the automation of planning, budgeting, forecasting and analysis processes using IBM TM1.

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IBM Cloud Pak for Data

The Cloud Pak for Data acts as a central, modular platform for analytical use cases. It integrates functions for the physical and virtual integration of data into a central data pool - a data lake or a data warehouse, a comprehensive data catalogue and numerous possibilities for (AI) analysis up to the operational use of the same.

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IBM Cognos Analytics 11

IBM Cognos Analytics is a central platform for the provision of dispositive information in the company. With the reporting and analysis functions of IBM Cognos, the relevant information can be prepared and used throughout the company.

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IBM Cloud Pak for Application

The IBM Cloud Pak for Application provides a solid foundation for developing, deploying and modernising cloud-native applications. Since agile working is essential for a faster release cycle, ready-made DevOps processes are used, among other things.

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IBM Db2

The IBM Db2database has been established on the market for many years as the leading data warehouse database in addition to its classic use in operations.

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IBM Netezza Performance Server

IBM offers Database technology for specific purposes in the form of appliance solutions. In the Data Warehouse environment, the Netezza technology, later marketed under the name "IBM PureData for Analytics", is particularly well known.

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IBM Cloud Pak for Automation

The IBM Cloud Pak for Automation helps you automate manual steps on a uniform platform with standardised interfaces. With the Cloud Pak for Business Automation, the entire life cycle of a document or process can be mapped in the company.

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Enterprise Service Management

Our Enterprise Service Management Solution offers you a way to make Service Management accessible to all participants via an easy-to-use service portal. You can map your processes in this portal according to defined procedures and connect them to other systems. In addition, you relieve the process participants through automation.

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IBM Cloud Pak for Data Accelerator

For a quick start in certain use cases, specifically for certain business areas or industries, IBM offers so-called accelerators based on the "Cloud Pak for Data" solution, which serve as a template for project development and can thus significantly accelerate the implementation of these use cases. The platform itself provides all the necessary functions for all types of analytics projects, and the accelerators provide the respective content.

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Bamboo, Bitbucket, Sourcetree

Continuous Integration and a Continuous Delivery Pipeline with Bamboo, Bitbucket and Sourcetree. We can help you with our years of experience as a user as well as a solution partner of Atlassian products in many areas.

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Standardized data management creates basis for reporting

TIMETOACT implements a higher-level data model in a data warehouse for TRUMPF Photonic Components and provides the necessary data integration connection with Talend. With this standardized data management, TRUMPF will receive reports based on reliable data in the future and can also transfer the model to other departments.

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IT Asset Management – Reducing Costs and Risks Sustainably

We help customers to increase the transparency of IT assets in use, identify potential savings for hardware and software, and avoid compliance risks at the same time.

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IT Controlling – Determination and allocation of IT costs

We help to make IT controlling processes efficient and effective and to introduce suitable procedures for the internal allocation of IT costs.

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Database technologies

Flexible, secure and fast database systems form the stable basis of your daily work. We manage your databases optimally.

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IBM Cloud Pak for Data System

With the Cloud Pak for Data System (CP4DS), IBM provides the optimal hardware for the use of all Cloud Pak for Data functions industry-wide and thus continues the series of ready-configured systems ("Appliance" or "Hyperconverged System").

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Mix of IASP & ILMT support for optimal license management

To minimize financial risk and personnel time, UTA resorts to proactive management of the license inventory (IASP) by TIMETOACT. In this way, not only will IBM license audits be avoided in the future, but TIMETOACT will also ensure compliance-compliant use of the ILMT as part of license management.

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Cloud Migration | Atlassian

The TIMETOACT team has been able to develop best practices as a result of a large number of migrations in recent years. These form the foundation of our standards, templates, scripts, and checklists and help you to move securely into the Cloud.

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Standardize and optimize project management | Atlassian

With defined standard templates, you can easily optimize your project management and use BigPicture to keep track of the status of your project, dependencies between tasks, and the planning and workload of your team.

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vdek introduces new Data Warehouse solution

The TIMETOACT GROUP supports the Verband der Ersatzkassen e. V. in the switch from a system environment to the latest IBM technology.

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Demand Management – Clarity on IT needs

We help to determine your effective IT needs, e.g. for workstations with Microsoft Office 365. Save money by only buying what you really need.

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IBM Watson® Knowledge Catalog/Information Governance Catalog

Today, "IGC" is a proprietary enterprise cataloging and metadata management solution that is the foundation of all an organization's efforts to comply with rules and regulations or document analytical assets.

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IBM InfoSphere Information Server

IBM Information Server is a central platform for enterprise-wide information integration. With IBM Information Server, business information can be extracted, consolidated and merged from a wide variety of sources.

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Data Vault Modeling Approach

Data Vault is a modeling technique that is particularly suitable for agile Data Warehouses. It offers high flexibility for extensions, complete historization of data and allows parallelization of data loading processes. Data Vault supports without significantly increasing the complexity of the Data Warehouse over time.

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Enterprise Architecture – Synchronising Business and IT

With pragmatic approaches and based on industry standards (TOGAF), we support clients in the introduction of an effective EAM.

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IT security – protection against cyber attacks

IT security is becoming more and more important. We help organizations to implement appropriate and effective security structures, processes and controls.

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Talend Real-Time Big Data Platform

Talend Big Data Platform simplifies complex integrations so you can successfully use Big Data with Apache Spark, Databricks, AWS, IBM Watson, Microsoft Azure, Snowflake, Google Cloud Platform and NoSQL.

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Talend Data Integration

Talend Data Integration offers a highly scalable architecture for almost any application and any data source - with well over 900 connectors from cloud solutions like Salesforce to classic on-premises systems.

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Talend Data Fabric

The ultimate solution for your data needs – Talend Data Fabric includes everything your (Data Integration) heart desires and serves all integration needs relating to applications, systems and data.

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Talend Application Integration / ESB

With Talend Application Integration, you create a service-oriented architecture and connect, broker & manage your services and APIs in real time.

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Application Modernization

Application Modernization focuses on modernizing existing applications. The key to success in Application Modernization is the strategy and selection of projects.

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IT Sourcing & Vendor Management – Managing IT Partners

We ensure the application of best practice methods for the selection and evaluation of IT vendors and service providers and for cost-optimized supplier management.

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Application Development

Application Development refers to the process of modifying, designing and/or developing one or more applications. Gaps in the software landscape can be closed by tailoring applications individually to the customer.

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Interactive online portal identifies suitable employees

TIMETOACT digitizes several test procedures for KI.TEST to determine professional intelligence and personality.

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IT Service Management – Optimal support for IT processes

IT should be customer and service oriented. We help you implement effective and efficient IT service management

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IT strategy – A clear goal and the way to achieve it

The IT strategy provides you with the plan for the long-term development of your IT organisation, necessary technologies, processes and digital culture.

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Requirement Engineering

Requirement Engineering, also known as Requirements Analysis, is a central component of the Software Development process. In this process, the requirements for the system to be developed are defined using a systematic procedure.

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TIMETOACT implements integrated insurance software

Less than one year from project start to system implementation: TIMETOACT developed the integrated, browser-based insurance software "HERMES" for the VOV D&O insurance association. The cross-departmental individual software completely covers all core processes of the insurance company. Users particularly appreciate the intuitive user interface and the high performance of HERMES.

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Advice around Mendix

Develop your solutions quickly and independently in low-code with the leading technology vendor. Use the Mendix toolkit and model your applications with visual elements.

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Advice around Mendix

Develop your solutions quickly and independently in low-code with the leading technology vendor. Use the Mendix toolkit and model your applications with visual elements.

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TIMETOACT simplifies reporting in IBM Cognos

In the course of modernizing the application for Bette GmbH & Co. KG, TIMETOACT individually expanded the filter and selection options in IBM Cognos to include important customer-specific functions. The family-owned company particularly benefits from the search and grouping function.

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Expedition zum Identity Management

Webcast: "Expedition zum Identity Management"

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Microsoft Azure Synapse Analytics

With Synapse, Microsoft has provided a platform for all aspects of analytics in the Azure Cloud. Within the platform, Synapse includes services for data integration, data storage of any size and big data analytics. Together with existing architecture templates, a solution for every analytical use case is created in a short time.

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Talend migration in record time

TIMETOACT migrated the Talend Data Integration Suite, including all workflows and processes, to the internal system environment of the municipal utility (with a subscription license) within a very short period of time and will continue to provide support as a support partner in the future if required.