Data may contain errors and specific master data related with every source, so multiple transformation tasks are needeed to be performed in order to give sence and reliability.

The day by day life of a data engineer is devoted to create APIs that facilitate data consumption, integragion of data sets from different sources and analyzing how data is used to improve quality, efficiency and processing speed.

Programing with Python, Java or Scala for connecting data from NoSQL and related databases is one of the most important task they perform. They use Hadoop and Spark technologies to improve data consumption processes and work intensively with tools such as NiFi, Sqoop, Flume, Ozie, Kafka, Talend, Pig, Hive, MongoDB, HBase, etc.

Data scientists use languages such as SPSS, R, SAS, and especially Python, Notebooks, PySpark, Anaconda, Pandas, NLTK, etc. to create models

Data Analysts are business savvies and are responsible for asking questions and finding answers through data by interpreting the insights of models designed by Data Scientists and feedback models with continuous improvement.

They also perform the visual representation of the data which plays a fundamental role in the communication of the results to the different interested parties and they are in charge of generating a story of the data helping the interpretation and understanding of the insights.

They work with data visualization tools such as Qlik Sense, Power BI or Tableau, creating dashboards, reports and data extractions for business.

Supervise the processes of ingesting, storing, processing, and transmitting data to internal and external target systems.

They set metrics and data quality requirements, including the definition of values, ranges and parameters that are acceptable for each data element in each use case.

They participate in continuous and detailed assessment of data quality, identification of anomalies and discrepancies, identification of root cause and implementation of corrective measures.

Establish guidelines and protocols governing data proliferation to ensure that privacy controls are applied in all processes. Define policies and procedures for data access, including authorization criteria based on role and/or profile.

They use a variety of tools ranging from ingest tools (Nifi, Sqoop, etc.) to data analysis tools. They usually work with Python and Pandas library.

They are the bridge between the teams of development and operations, who contributes with their knowledge of the production environment in order to design the testing and staging environments.

They ensure that the development made by developers works right away across a diverse set of operating systems and platforms.

Traditional solutions are based on the limitation of the functionality where the user has access, with the consequent deterioration of productivity and the increase of the costs involved.

Also, these traditional solutions rely on the use of antivirus, which are valid to detect known malware, not being equally effective for the detection of new malware, as many people could verify with threats such as WannaCry and other Randomware attacks that were introduced in large companies that could brag about a high level of security of their entire infrastructure.

Indizen collaborates with Simarks Software, a Spanish start-up focused on endpoint protection, distribution and evolution of its cybersecurity solutions, where Simarks BestSafe stands out.

BestSafe is a business and domestic solution that allows management of the privileges of users and applications on computers, generating an execution framework that avoids the effects of malware even if it is an unknown one:

Centrally manage user permissions on their computers.

Based on the definition of rules for each user, group or organization.

Create a secure execution framework against unknown malware or ransomware.

You do not need to inspect each file or process to be executed, so it does not slow down the equipment.

It does not replace antivirus but complements them.

It does not reduce employee productivity unlike traditional models based on total reduction of privileges.

In most organizations, the task of determining and managing who can do what (authorization) in all of their web applications is delegated to each application, therefore having a decentralized management has, among others, the following disadvantages:

It is difficult to obtain or maintain the catalog of functionalities offered by the applications and authorized users for each of the functionalities.

Change management when adding new policies or when there is a change in the roles and their propagation through the different applications requires a great effort of development, deployment, tests, etc.

Indizen collaborates with Dulin Technologies, a Spanish company specialized in the development of applications, in the development of a centralized management platform of privileges in applications that offer the following functionalities:

A centralized repository of functionalities and the management tools necessary to have the catalog of applications, the functionalities by application as well as the privileges of the users and roles of the active directory in those applications.

A rule engine that allows you to design the authorization rules for each functionality as well as its application in real time.

A set of services that allows applications to query the privileges of a user or role in real time.

A framework that facilitates the integration in time of development of the applications in the system of centralized management of privileges.

The Development Team evaluates your development capability in the Sprint. The Product Owner explains the objective of the iteration, and the items of the Backlog that should be done to achieve the final objective. The whole team works collaboratively to understand the work to be done. During Sprint Planning the Sprint Goal is defined, which is the objective that the Scrum team must achieve for the correct evolution of the project.

With Sprint Goal and the selected Product Backlog items (Sprint Backlog), the development team decides how to turn these user stories into product increment. At the end of the meeting, the development team should be able to explain to both the Product Owner and the Scrum Master how they are going to work in a self-organized way to develop all the items of the Sprint Backlog, and achieve the target defined in the Sprint Goal.