Vatten är en livsviktig resurs därför behöver kvalitén övervakas. Slamhalt i vatten är viktigt eftersom det kan föra med sig gifter och näringsämnen, men även grumlar vattnet vilket kan påverka livsmiljön för vattenlevande organismer. Slamhalt varierar över tid på grund av olika processer som transporterar material till vattendrag. För att mäta slamhalten har man historiskt tagit vattenprover i fält. Det är tidsödande och görs sällan vilket leder till att man lätt missar toppar och dalar i flödet.  Turbiditet är möjligt att mäta in situ och innebär att vattnets ljusgenomsläpplighet mäts. Det kan mätas med täta intervall vilket ger detaljerad information om förändringar i vattendragen. Korrelationen mellan turbiditet och slamhalt har undersökts flera gånger men eftersom mätningar reagerar på partiklars storlek och form behöver man utvärdera sambandet för varje enskilt vattendrag.  2017 gjordes en studie för Sveriges lantbruksuniversitet där Hoang (2017) använde multivariabel statistik för att undersöka turbiditet korrelerat med fosfor samt jordarters och markanvändnings påverkan på relationen i svenska vatten.  Sedan dess har markdata uppdaterats vilket gör det aktuellt att undersöka korrelationen mellan slamhalt och turbiditet. Genom linjär regression visades ett tydligt samband mellan turbiditet och slamhalt för många avrinningsområden. De högsta korrelationerna syntes för områden med hög fördelning av åkermark och lerhalt. / Water is a vital resource for life, that is why water quality is monitored. Suspended solids in water are important because it transports pollutants and nutrients, it also dims the water which can affect the environment for water living organisms. Suspended solids change over time due to different processes that transport materials to waterbodies. Historically, suspended solids have been measured by taking samples in the field. That takes a lot of time and fluctuations are lost because of dispersed measuring periods.  Turbidity can be measured in-situ and quantifies the light attenuation of the water. It can be measured with tight intervals which results in detailed information about changes in the waterbody. The correlation between suspended solids and turbidity has been studied several times, however, a turbidity sensor reacts to particle size and form which means that the correlation needs to be investigated for every individual waterbody.  2017 a study at the Swedish university of agriculture was done where Hoang (2017) used multivariate statistics to study turbidity correlated with phosphorus, as well as soil classes and land use factors influence on the relationship in Swedish waters. Since then, new data for soil and land use have been updated which makes it relevant to evaluate the correlation between suspended solids and turbidity. Through linear regression a clear correlation was shown for many catchments. The highest correlations were found in areas with high rates of agriculture and clay rich soils.

Data Integration is currently an important and complex topic for many companies, because having a good and working Data Integration solution can bring multiple advantages over competitors. Data Integration is usually being executed in a form of a project, which might easily turn into failure. In order to decrease risks and negative impact of a failed Data Integration project, there needs to be good project management, Data Integration knowledge and the right technology in place. This thesis provides a framework for setting up a good Data Integration solution. The framework is developed based on the current theory, currently available Data Integration tools and opinions provided by experts working in the field for a minimum of 7+ years and have proven their skills with a successful Data Integration project. This thesis does not guarantee the development of the right Data Integration solution, but it does provide guidance how to deal with a Data Integration project in a large enterprise. This thesis is structured into seven chapters. The first chapter brings an overview about this thesis such as scope, goals, assumptions and expected value. The second chapter describes Data Management and basic Data Integration theory in order to distinguish these two topics and to explain the relationship between them. The third chapter is focused purely on Data Integration theory which should be known by everyone who participates in a Data Integration project. The fourth chapter analyses features of the current Data Integration solutions available on the market and provides an overview of the most common and necessary functionalities. Chapter five focuses on the practical part of this thesis, where the Data Integration framework is designed based on findings from previous chapters and interviews with experts in this field. Chapter six then applies the framework to a real working (anonymized) Data Integration solution, highlights the gap between the framework and the solution and provides guidance how to deal with the gaps. Chapter seven provides a resume, personal opinion and outlook.