Discover and grow revenue streams by identifying risks and trends. Extend your data investments by seamlessly integrating enterprise and cloud data. Optimize internal business processes with KPI validation and analysis.
The Database Engine component of SQL Server is the core service for storing, processing, and securing data. The Database Engine provides controlled access and rapid transaction processing to meet the requirements of the most demanding data consuming applications in your enterprise.
Microsoft Integration Services is a platform for building enterprise level data integration and data transformations solutions. Use Integration Services to solve complex business problems by copying or downloading files, loading data warehouses, cleansing and mining data, and managing SQL Server objects and data.
Installed as an on-premises server instance, SQL Server Analysis Services supports tabular models at all compatibility levels (depending on the version), multidimensional models, data mining, and Power Pivot for SharePoint.
SQL Server Reporting Services (SSRS) provides a set of on-premises tools and services that create, deploy, and manage mobile and paginated reports.
Machine Learning Services is a feature in SQL Server that gives the ability to run Python and R scripts with relational data. You can use open-source packages and frameworks and the Microsoft Python and R packages for predictive analytics and machine learning. The scripts are executed in-database without moving data outside SQL Server or over the network.
Power BI is a business analytics service that delivers insights to enable fast, informed decisions. Quickly go from data to insight to action. Connect to hundreds of sources, prep data with ease, and create beautiful reports, all in minutes.
ArcGIS provides contextual tools for mapping and spatial reasoning so you can explore data and share location-based insights.
Azure SQL Database is an intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility.
QL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data. SQL Data Warehouse is a key component of a big data solution.
Azure Data Lake Storage Gen2 is a highly scalable and cost-effective data lake solution for big data analytics. It combines the power of a high-performance file system with massive scale and economy to help you speed your time to insight.
Azure Stream Analytics is a real-time analytics and complex event-processing engine that is designed to analyze and process high volumes of fast streaming data from multiple sources simultaneously. Patterns and relationships can be identified in information extracted from multiple input sources including devices, sensors, clickstreams, social media feeds, and applications.
Azure Data Factory is a service built for all data integration needs. It is used to construct ETL and ELT processes and to visually integrate data sources by using more than 80 natively built and maintenance free connectors.
Azure Data Catalog is a fully managed cloud service that lets users discover the data sources they need and understand the data sources they find. At the same time, Data Catalog helps organizations get more value from their existing investments.
Azure Machine Learning is a cloud service that you use to train, deploy, automate, and manage machine learning models at cloud scale. The service fully supports open-source technologies such as PyTorch, TensorFlow, and scikit learn and can be used for any kind of machine learning, from classical ml to deep learning, supervised and unsupervised learning.
Azure Data Lake Analytics is an on-demand analytics job service that simplifies big data. Instead of deploying, configuring, and tuning hardware, queries are written to transform data and extract valuable insights. The analytics service can handle jobs of any scale instantly by setting the dial for how much power is needed. You only pay for your job when it is running, making it cost-effective.
Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services platform. Designed with the founders of Apache Spark, Databricks is integrated with Azure to provide one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.
Azure Cognitive Services enable developers to easily add cognitive features into their applications. The goal of Azure Cognitive Services is to help developers create applications that can see, hear, speak, understand, and even begin to reason. The catalog of services within Azure Cognitive Services can be categorized into five main pillars - Vision, Speech, Language, Web Search, and Decision.
Azure Machine Learning Studio is a collaborative, drag-and-drop tool for building, testing, and deploying predictive analytics solutions with your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Power BI.
Azure Cosmos DB is Microsoft's globally distributed, multi-model database service. Cosmos DB enables you to elastically and independently scale throughput and storage across any number of Azure regions worldwide and take advantage of fast, single digit millisecond data access using your favorite APIs including SQL, MongoDB, Cassandra, Tables, or Gremlin.
Both Azure IoT Hub and Azure Event Hubs are cloud services that can ingest large amounts of data and process or store that data for business insights. The two services are similar in that they both support the ingestion of data with low latency and high reliability, but they are designed for different purposes. IoT Hub was developed to address the unique requirements of connecting IoT devices to the Azure cloud while Event Hubs was designed for big data streaming.
Created as an Azure resource, Azure Analysis Services resources support tabular models at the 1200 and higher compatibility levels. DirectQuery, partitions, row-level security, bi-directional relationships, and translations are all supported.
KiZAN was involved in testing installations of the On-Premise Report Server environments. Multiple departments wanted to switch from SSRS to Power BI very quickly, and KiZAN was able to meet those needs. One way to achieve this was to integrate Power BI reports to SSRS reports using hyperlinks. It was also accomplished by passing URL parameters to Power BI On-Premise Report Server to filter data sets.
Coats, the world’s leading industrial thread manufacturer and textile leader, trusted KiZAN to develop intelligent dashboards to deliver real-time and historical KPI insights for a variety of business users. The solution supports high-level and granular visualizations for easy comprehension of current statuses and historical trends and provides alerts for key manufacturing processes.
The reports leverage existing cloud-based data repositories and data streams, such as Azure Analysis Services, Azure SQL Data Warehouse, Azure Data Lake Store, Azure Stream Analytics and Azure Cosmos DB.
With a perishable inventory of advertising timeslots, Raycom Media has a slim and unforgiving window to maximize advertising revenue. It is necessary to predict demand and accurately set pricing for programming months in advance. Historically, however, pricing has been established solely by human intuition.
ServiceMaster was seeking a solution to provide real-time insight into vast streams of data collected through multiple line of business applications, call center operations, web sites and third-party services in order gain immediate visibility of the relationship between operations and sales performance.
Systems & Data