In the following webcast, we will talk to Andrew Brust, Senior Director of Market Strategy and Intelligence in Datameer.
We will learn about Hadoop ecosystem and PaaS options in Azure, difference of Data Lake and Data Warehouse, and added value of unstructured datastreams. We will discuss Hadoop learning curve for professionals with OLTP database and BI background, and how Datameer can help to create big data solutions and futureproof against the change.
Technologies: HDInsight, Stream Analytics, Azure Data Lake Store and Analytics, Azure Machine Learning and Power BI.
To access the webcast, you will need to fill small registration form.
Modern EDW should be able to manage both structured and unstructured data to realize full value of data. Security, consistency, and credibility of data is also very important. Data warehouse and big data solutions from Microsoft provide a trusted infrastructure that can handle all types of data, and scale from terabytes to petabytes, with real-time performance.
In this webcast with participation of Mark Lochbihler (Director of Partner Engineering, Hortonworks) we discuss modern enterprise data warehouses (EDW) and migration to Microsoft Cloud (Azure). We will learn about the process, tools, and reference architectures for data warehouse migration.
To access the webcast, you will need to fill small registration form.
In this blog post, we will look at analysis of stock prices and dividendsby industry. This task is important to all participants of Stock Market including individual retail investors, institutional investors such as mutual funds, banks, insurance companies and hedge funds, and publicly traded corporations trading in their own shares.
In this demo, team of Stock Trading Company analyses semi-structured stock data from the New York Stock Exchange (NYSE).
Data Architect collects data and makes information accessible to business. He will use Hadoop-based distribution on Windows Azure and Hive queries to aggregate stock and dividend data by years.
Financial Analyst will analyze stock data and prepare ad-hoc reports to support trading and management processes. She will use Power Query add-in for Excel to join aggregated data from Hadoop with additional information on top 500 S&P companies from Azure Marketplace Datamarket. Additionally she will create ad-hoc reports with Power View for Excel.
Trading Executive is responsible for understanding key decision makers and suggesting best product mix of securities. He will make some modifications to Power View reports provided by Financial Analyst.
Details on how Data Architect aggregates data in Hadoop are available in a separate blog post.
When we a talking about Big Data we may mean huge amounts of data (high Volume), data in any format (high Variety), and streaming data (appearing with high Velocity). Microsoft provides solutions for all of these “3V” tasks under unified monitoring, management and security, as well as unified data movement technologies. These
workloads are supported correspondingly by SQL Server Database and Parallel Data Warehouse, HDInsight (Hadoop for Windows or Azure), and Microsoft SQL
Server StreamInsight.
Let us talk about Microsoft Big Data technology for Non-Relational data.
Microsoft’s adaptation of Hadoop technology can be deployed in a cloud-based environment or on-premises. The Hadoop-based service on the Windows Azure platform is a cloud-based service that offers elastic (in a term of data volumes) analytics on Microsoft’s cloud platform. For customers who want to keep the data within their data centers, Microsoft provides Hadoop-based distribution on Windows Server.
In this blog post, we will start diving into Hadoop in Azure technology and Hive queries to analyze semi-structured data in Hadoop.
In addition to traditional data warehousing, when operational data stored in special structures in Enterprise Data Warehouse, we can store all other raw data in “Store it All” cluster. At any moment, we are able to create query to these data to answer some business question. (In addition, we may store the answer in the Data Warehouse if necessary)
Let me introduce the first part of Bid Data Demonstration where Data Architect will store log files with stock prices and dividends in Azure Blob Storage and will use Hive queries to aggregate data by years and stock tickers into separate file.
Business Excellence 