Welcome to Panacee.tech

We provide organizations with help
on two important IT subjects

Enterprise Architecture

Enterprise Data Management

is a discipline for proactively and holistically leading enterprise responses to disruptive forces by identifying and analyzing the execution of change toward desired business vision and outcomes. (Source: Gartner).

is an organization’s ability to accurately define, easily integrate, and effectively retrieve data for both internal applications and external communications. (Source: Wikipedia)

Enterprise Architecture

Enterprise Data Management

is an organization’s ability to accurately define, easily integrate, and effectively retrieve data for both internal applications and external communications. (Source: Wikipedia)

Within the context of Enterprise Architecture, we have a specialization on Enterprise Data Management.

So, what’s this Enterprise Data Management?

Well, to be precise, Enterprise Data Management focuses on creating accurate, consistent, and transparent content. Emphasizing data precision, granularity and meaning, Enterprise Data Managment is concerned with how content is integrated into business applications and how it is passed from one business process to another.

Maybe it’s best explained with the use of a logical diagram

So, what’s this Enterprise Data Management?

We use a simple, market-compliant approach in which we distinguish four types of data.

Why is this important and what kind of data exists in our organization?

Structured

The first type of data that appeared was structured data. For the most part, structured data was a byproduct of transaction processing. A record was written when a transaction was executed. This could be a sale, payment, phone call, banking activity, or other transaction type. Each new record had a similar structure to the previous record.

Think of a deposit at a bank, to see the processing agreement: A bank customer walks to the counter and makes a deposit. The next person comes to the window and also makes a deposit. Although the account numbers and deposit amounts are different, the structures of both records are the same. We call this "structured data" because the same data structure is repeatedly written and rewritten.

With structured data, we typically deal with a large amount of records: one for each transaction that has taken place. It goes without saying that a high degree of business value is attached to structured data.

Semi-Structured

The main reason why plain text is not very useful is that plain text must also contain context in order to be understood. Therefore, it is not enough to just read and analyze raw text.

To analyze text, we need to understand both the text and the context of the text. However, we need to consider other aspects of text. We have to remember that text exists in a language, such as English, Spanish, German, etc. Also, some text is predictable, but other text is not predictable. Analyzing predictable text is very different from analyzing unpredictable text.

Another obstacle to sharp analysis is that the same word can have several meanings. The word "record" can mean a vinyl recording of a song in English. Or it could mean the speed of a race. But other language-related obstacles can also arise when we try to read and analyze a raw text.

Unstructured

IOT (Internet of Things) is the set of devices that are in contact with other devices or systems via internet connections and exchange data with them.

To be able to exchange data via the internet and thus with other devices or systems, the data must first be converted to a digital format. The operation of a machine, such as a car, watch or production machine, creates analog data. As long as the machine is running, it spits out measurements. The measurements can be of many things: temperature, chemical composition, speed, time of day, etc. In fact, the analog data can be of many different variables that are measured and recorded at the same time.

This often means an analog sensor, but when it can also convert this analog data into a digital format and is able to share it with other devices or systems, we generally speak of an IOT device.

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At Panacee we developed a four-layer DataFrameWork that can blend-in all 4 mentioned datatypes.

The DataFrameWork splits the functionalities and purposes both logically and technically into four distinct entities.

We deliver services on four layers concerning your data

DCL

Data Collaboration Layer

DAL

Data Acces Layer

DSL

Data Storage Layer

HPL

Hosting Platform Layer

We deliver services on four layers concerning your data

DCL

Data Collaboration Layer

DAL

Data Acces Layer

DSL

Data Storage Layer

HPL

Hosting Platform Layer

The services from Panacee are grouped and offered per horizontal layer as is displayed below

As you can see, we offer a different set of services in every layer of your data analyse. This way we can structure your data landscape.

Organizations need a data platform solution that can manage all types of data. Whether it’s structured, semi-structured, unstructured or streaming data.

The products and services that can be delivered with our Panacee services are amongst others; BI/Analytics services including dashboards for management reports, real-time data applications, data science products and services offered by our preferred DSML platform and machine learning products and services such as predictive models

Curious about what we can do for you? Get in touch! We are happy to advise you.

Contact information

Fill up the form and our team will get back to you within 24 hours.

Welcome to Panacee.tech

We provide organizations with help on two important IT subjects

Enterprise Architecture

Enterprise Data Management

Enterprise Architecture

Enterprise Data Management

Within the context of Enterprise Architecture, we have a specialization on Enterprise Data Management.

So, what’s this Enterprise Data Management?

Maybe it’s best explained with the use of a logical diagram

So, what’s this Enterprise Data Management?

We use a simple, market-compliant approach in which we distinguish four types of data.

Why is this important and what kind of data exists in our organization?

At Panacee we developed a four-layer DataFrameWork that can blend-in all 4 mentioned datatypes.

We deliver services on four layers concerning your data

DCL

Data Collaboration Layer

DAL

Data Acces Layer

DSL

Data Storage Layer

HPL

Hosting Platform Layer

We deliver services on four layers concerning your data

DCL

Data Collaboration Layer

DAL

Data Acces Layer

DSL

Data Storage Layer

HPL

Hosting Platform Layer

The services from Panacee are grouped and offered per horizontal layer as is displayed below

Organizations need a data platform solution that can manage all types of data. Whether it’s structured, semi-structured, unstructured or streaming data.

Curious about what we can do for you? Get in touch! We are happy to advise you.

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We provide organizations with help
on two important IT subjects