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Whether you are a strategist, coder, analyst, or a future-enthusiast, you will find a home at TietoEVRY. With us, you can make your mark and shape the future.

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Shape the future today

Shape the future today

Local proximity, global capabilities

When sailing in rough weather, being on the biggest ship at sea may seem the best option. But you'll soon discover that, unlike smaller ships, it isn’t agile enough to make sharp turns or enter tinier ports. With us, you get the best of both worlds.

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Shape the future today

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Customers want seamless digital solutions and agile teams. With us, they get just that. Our communities are not nurtured by corporate structures and are driven by passionate people at the front line. It’s hard to beat that combination.

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Shape the future today

Right conditions, great opportunities

“Ready to jump off a cliff? Get out of the comfort zone? Sure, but I prefer actually wearing the parachute”. Often these metaphors are used for describing development. But serious companies don’t throw people off cliffs. They have a plan.

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LEARN TO SPEAK DATA #4 ​ Do you easily get lost in the jungle of data terms? To help you out, we put together a data glossary so you can comfortably take a deep dive into the fascinating world of data. You can find the previous posts in the feed! ​ 1️⃣ Data and analytics platforms. A modern, cloud-based data and analytics platform combines traditional reporting with modern analytics and data scientists' services. It provides a platform, for example, for data-based applications that use artificial intelligence.​ 2️⃣ Industry 4.0 is a vision of an advanced industry where ecosystems, the industrial Internet, modern technology, and new business models are leveraged. The vision is based on the digital transformation of traditional manufacturing and production methods.​ 3️⃣ Predictive analysis. Machine learning and statistical methods allow us to model future events based on the data of previous events. Such modeling is called predictive analytics. Typical applications for predictive analytics can be, for example, customer attrition expectations, financial data predictions, and predicting machinery maintenance needs.​ Hungry to learn more? Check out the whole data glossary via link in bio! #data #dataglossary #digitaladvantage #datainsiders​

tietoevry 31 Jul

LEARN TO SPEAK DATA #3 ​ ​ Do you easily get lost in the jungle of data terms? To help you out, we put together a data glossary so you can comfortably take a deep dive into the fascinating world of data. You can find the previous posts in the feed! ​ ​ 1️⃣ The difference between a data warehouse and a data lake. ​ A data warehouse supports the organization's traditional core functions and obtains answers to defined questions from known source data. A data lake supports a more predictive and experimental approach. A data warehouse is mainly for structural information processing. A data lake enables the processing of all kinds of data in the organization.​ ​ 2️⃣ Data lifecycle refers to the different stages of data elements and data resources from the creation of information to its destruction. The stages can include storing, warehousing, transferring, using, and archiving the information.​ ​ 3️⃣ A data pipeline is a controlled function for data processing and data product creation that brings business value. A data product can be, for example, a report or a prediction produced by a machine learning algorithm that’s used via an interface.​ ​ Are you hungry to learn more? Check out the whole data glossary via link in bio! #data #dataglossary #digitaladvantage #datainsiders

tietoevry 24 Jul

LEARN TO SPEAK DATA #2 ​ Do you easily get lost in the jungle of data terms? To help you out, we put together a data glossary so you can comfortably take a deep dive into the fascinating world of data. 1️⃣Data management in manufacturing. The business of manufacturing companies depends on building equipment that is either sold or rented to a customer. Such companies collect plenty of information about their business operations. If this data is managed properly, the life cycle of devices can be accurately modeled.​ ​2️⃣ Data governance is about data ownership. The owner of a company's business units, equipment, and properties manages the usage of the company's assets and strives to maximize its business benefits. This should also be the case with company-owned data sets. The owner of a data set is responsible for ensuring the data is of good quality and making sure the user rights comply with the set rules. ​ ​3️⃣ Data architecture is a part of the overall architecture and can refer to several perspectives. It often relates to the artefacts of data architecture on multiple abstraction levels, such as data models, definitions, and descriptions of information flows and metadata.​ ​Are you hungry to learn more? Check out the whole data glossary: link in bio #datainsiders

tietoevry 21 Jul

We present: Annas top 5 tips on how to create employee engagement without meeting up physically: 1. Build trust with your colleagues. 2. Be transparent. The need for information is only growing as we continue to work remote. Share all information you can, even if it’s «unnecessary». 3. Involve. When you involve in different project you will develop and grow professional skills. 4. Learn to work efficiently with digital workshops. 5. Let your colleagues see who you are. At work and at home.

tietoevry 13 Jul

LEARN TO SPEAK DATA #1 ​ Do you easily get lost in the jungle of data terms?🐻🐯🐨🐵🦁To help you out, we put together a data glossary so you can comfortably take a deep dive into the fascinating world of data. ​1️⃣ A data-driven approach means that an organization makes decisions based on information (data!). Being able to make data-driven decisions requires reliable and accessible data. Having the technology and systems is not enough—success requires people, and cultural changes. ​ 2️⃣ A business transformation aims for fundamental changes in a business or its processes. A data-driven business transformation uses data and analytics to enable those changes. It means not only deploying the technology but also developing data availability, data quality, procedures, and a data-driven culture.​ ​3️⃣ A data ecosystem is an open or closed network with an interest in exchanging data between the actors of the network, following common rules: interfaces and data models. The members of an ecosystem have one thing in common: they all benefit from the data so much that it's worth sharing their data with the network. Being involved in a suitable data ecosystem or owning one can, at best, be a significant competitive advantage.​ Are you hungry to learn more? Check out the whole data glossary. Link in bio

tietoevry 10 Jul

One of the key enablers of the digital economy and drivers of digital ecosystems is external data sharing and exchange. Join 15 minutes on Digital Advantage on July 8 at 11:45 CET to learn more – sign up via link in bio!☝🏼 #digitaladvantage #data #datasharing

tietoevry 06 Jul
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