Improved Analytics With Optimized
Data Warehouse Solutions

Making informed business decisions requires access to accurate KPIs (key performance indicators). In order to monitor your KPIs, you’ll need to analyze massive sets of data. The challenge lies in the fact that all of this data is stored in separate systems and often in different formats, which makes it difficult to not only collect and analyze data efficiently, but to do so accurately. Setting up a data warehouse allows you to collect and integrate data from all of your different data sources, thereby creating a centralized gateway that makes it possible to perform accurate analytics on a large scale. Here at Cyber Group, our team of consultants can help provide the data warehouse solutions that your company needs.

Our Distinctive Process to
Data Warehouse

Traditional data loading and ETL (extract, transform, and load) processes are known for being time-consuming and prone to errors. It’s why we employ our own distinctive process for data warehousing that will enable you to collect, evaluate, and analyze your data in a more effective and efficient manner.

Our team will begin by performing a thorough assessment of your BI capabilities, including evaluations of your current processes, systems, and more. We will then create a roadmap that outlines a plan for implementing a data warehousing solution that will meet your specific needs. We’ll include these items on your roadmap:

 

Budget

Different companies have different budgets to work with. We will take into consideration your organization’s budget when planning your data warehouse solution.

 

Timeline Constraints

It can take some time to implement a comprehensive data warehousing solution that’s properly integrated with all of your data sources and making sure that your data warehouse fits your BI strategy. Fortunately, it’s not all or nothing. We will build our roadmap based on your timeline constraints by prioritizing certain tasks over others.

 

Infrastructure

Every data warehouse has its own parameters and its own unique features. We will help design the infrastructure of your data warehouse to address your specific needs. This includes setting up reporting complexity, data volume, number of users, ETL, and system availability. We can also build your data warehouse on your premises or on the cloud.

At Cyber Group, we offer comprehensive data warehouse services, including designing your data warehouse solution, developing it, and implementing it.

 

Design

Careful planning of your data warehouse solution is critical. Data warehouses can take a long time to construct because of how challenging it can be to populate and maintain them. After locating your data sources and planning your data transformations, the tracking duration must be set (which establishes how long data should be archived).

 

Develop

Because data warehouse projects are so large and you may have certain time constraints, we will establish a phased delivery schedule to follow as we develop your data warehouse solution.

 

Implement

We will use intelligent matching techniques to automatically map your source entities to the destination. Once implemented, you will be able to use direct maps or write custom expressions due to the platform’s balanced combination of automation and customization. You will be able to choose your data loading strategy or deploy a custom read strategy by defining the rules yourself.

As far as data warehousing tools go, we are not beholden to any specific software. Our team of developers have extensive experience and expertise working with a variety of data warehousing tools, including some of the top RDBMS (relational database management systems) favored throughout the industry, such as Microsoft SQL and Oracle.

 

Microsoft SQL

Microsoft’s RDBMS is known as Azure SQL. Their platform allows you to create indexes, partitions, and stored procedures, making it easy to migrate to the cloud. Azure SQL can also scale compute power and storage independently, which means that you would only pay for the query performance you need. Other features include dynamic pause, which allows you to ramp down compute while persisting the data, thereby optimizing your compute infrastructure’s utilization. Its Polybase feature makes it easy to combine data sets. Azure SQL can also be easily integrated with Azure Machine Learning, Microsoft Power BI, and Azure Data Factory. Its hybrid infrastructure allows for an on-premise or cloud-based data warehouse solution.

 

Oracle

The Oracle object-relational database engine can run on all platforms on numerous operating systems. It’s known for its stability and ability to scale. It’s suitable for businesses of all sizes because it allows the management of relational databases, from simple to large sets of data. Functionality includes the ability to provide alerts, make backup copies, manage users (keeping data secure), and use partitions (to improve replication and efficiency). It is somewhat expensive. It’s also easy to misconfigure if you don’t have experience using Oracle to set up data warehouses, resulting in slow performance times. A professional team of consultants to aid you in designing, developing and implementing an Oracle-based data warehouse is recommended.

 

Other RDBMS

We use many other data warehouse solutions as well, including popular alternatives to Oracle and Azure, such as Amazon Redshift and Cloudera EDH (enterprise data hub).

Enterprise-level companies have a much larger volume of data from a larger number of sources. This can require considerably more resources. There are a number of solutions on the market that cater specifically to handling big data. Our data warehouse consultants and developers can work with these big data solutions:

 

Hadoop Cluster

Hadoop Cluster was designed to store and analyze huge volumes of unstructured data in a distributed computing environment. A cluster is a group of servers that function as a single system and enable high availability, load balancing, and parallel processing. Hadoop itself is an open source distributed processing software. Hadoop Cluster is therefore capable of increasing the speed of data analysis applications, is very scalable, and if the volume of data is increasing significantly, additional cluster nodes can be added to help increase throughput. Every piece of data is also copied onto other cluster nodes so data is not lost if one of the nodes fails. If you are dealing with big data, we can implement a Hadoop Cluster solution.

 

Data Lakes Implementation

Data Lake is a centralized repository where you can store your data whatever the volume might be. You can store your data without structuring it and still run dashboards, visualizations, real-time analytics, machine learning, and big data processing. It’s a potentially effective alternative to implementing a data warehouse for businesses who need big data capabilities.

Enterprise-level companies have a much larger volume of data from a larger number of sources. This can require considerably more resources. There are a number of solutions on the market that cater specifically to handling big data. Our data warehouse consultants and developers can work with these big data solutions:

 

Hadoop Cluster

Hadoop Cluster was designed to store and analyze huge volumes of unstructured data in a distributed computing environment. A cluster is a group of servers that function as a single system and enable high availability, load balancing, and parallel processing. Hadoop itself is an open source distributed processing software. Hadoop Cluster is therefore capable of increasing the speed of data analysis applications, is very scalable, and if the volume of data is increasing significantly, additional cluster nodes can be added to help increase throughput. Every piece of data is also copied onto other cluster nodes so data is not lost if one of the nodes fails. If you are dealing with big data, we can implement a Hadoop Cluster solution.

 

Data Lakes Implementation

Data Lake is a centralized repository where you can store your data whatever the volume might be. You can store your data without structuring it and still run dashboards, visualizations, real-time analytics, machine learning, and big data processing. It’s a potentially effective alternative to implementing a data warehouse for businesses who need big data capabilities.

Our Services Help You
Analyze Disparate Data

The accuracy of your analytics depends on your ability to collect accurate data from all of your data sources. A data warehouse solution can ensure accuracy across the board. We can help you determine what your data warehouse needs are as well as design, develop, and implement a data warehouse solution using whatever RDBMS fits your needs best.

We Help Your Business Integrate Data And Make Better Business Decisions

Businesses tend to collect massive amounts of data that can be leveraged to make better business decisions. The problem is that this data is often isolated in different locations and in different formats. Our data warehouse solutions can help you integrate your data to ensure that you obtain valuable insights analyzed from accurate data in a fast and effective manner.

Improve your Data Warehouse ROI. Contact a
consultant today.