A Buyer’s Guide to Selecting Data warehouse platform, software or tool

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Raj Joseph - May 28, 2019

Data Warehouse

buyer guide to data warehouse

Introduction

The importance of data warehouse platforms to every organization cannot be overemphasized. A data warehouse is a centralized store for all data generated by different departments in an organization. A data warehouse platform enables an organization to analyze its historical data overtime and provide users with multiple views of information in an easy to read matter. With a data warehouse platform, all organizations can gain insights useful in making business decisions.

Evaluating your need for a data warehouse platform

Some of the significant benefits of having a data warehouse platform include the following:

• Better decision making: Data warehouse helps organizations store an enormous amount of data, facts, statistics which can be retrieved by decision makers. With this, corporate decision makers will no longer make take decisions based on a limited amount of data. 

• Easy access to data: Data warehouse also provides easy and quick access to information for business users, which is very important when trying to stay ahead of your competitors. With data warehouses, additional time will not be spent on retrieving data from multiple sources because all users have access to accurate data with little or no support from the IT department.

 • Data quality and consistent result: Data warehouses collect data from different sources and convert them to widely used format for all departments; this makes it possible for various departments to produce consistent results which are accurate and necessary for making tough business decisions. 

• Insight into organizations performance: Data warehouse also provides insight into the historical performance of an organization. Data analyst and business users can get information like business trends, customer’s behaviors, and annual sales from a data warehouse.

• Answer questions about your business: Data warehouse also helps a business owner answer accurately different questions about their business. It collects data from various sources despite the location and collates them into a single platform which can be used by business leaders to gain insight into an organizations activity. 

• Improves operational workflow: Data warehouse also helps to improve operational workflow. This is because data kept in a warehouse is usually evaluated, transformed, and cleansed, and the quality of information that can be generated from such data is high and accurate.

• Better decision making: Data warehouse helps organizations store an enormous amount of data, facts, statistics which can be retrieved by decision makers. With this, corporate decision makers will no longer make take decisions based on a limited amount of data. 

• Easy access to data: Data warehouse also provides easy and quick access to information for business users, which is very important when trying to stay ahead of your competitors. With data warehouses, additional time will not be spent on retrieving data from multiple sources because all users have access to accurate data with little or no support from the IT department.

 • Data quality and consistent result: Data warehouses collect data from different sources and convert them to widely used format for all departments; this makes it possible for various departments to produce consistent results which are accurate and necessary for making tough business decisions. 

• Insight into organizations performance: Data warehouse also provides insight into the historical performance of an organization. Data analyst and business users can get information like business trends, customer’s behaviors, and annual sales from a data warehouse.

• Answer questions about your business: Data warehouse also helps a business owner answer accurately different questions about their business. It collects data from various sources despite the location and collates them into a single platform which can be used by business leaders to gain insight into an organizations activity. 

• Improves operational workflow: Data warehouse also helps to improve operational workflow. This is because data kept in a warehouse is usually evaluated, transformed, and cleansed, and the quality of information that can be generated from such data is high and accurate.

Criteria to consider when choosing a data warehouse platform

Some of the criteria’s to consider when choosing a data warehouse platform includes the following

• Performance: When selecting a data warehouse, it is vital to consider the performance of the data warehouse platform. The platform must be able to optimize queries from an operation or transaction database management system (DBMS). By looking at performance, you will also consider the scalability of the platform; this is because infrastructural scalability is also very important for every company that is building on massive growth. There are so many data warehouse platforms that provide an easy to scale cluster while others scale seamlessly in the background. 

• Reliability: Reliable and professional support is a significant criterion you must consider when choosing a Data warehouse platform; it is vital to look at how quickly and thoroughly a vendor responds during downtime.

 • Usability and Security: As your business grows, the number of data sources for your business also increases. Therefore you need a data warehouse platform that has some features and functions that includes locking schemes, remote maintenance capabilities, monitoring utilities, user chargeback, DBA productivity tools, and another security mechanism

• An organization needs: You must also consider your needs carefully before choosing the type of data platform that supports your organizations need. Some platforms support multiple data sources that range from analytical databases, relational to NoSQL, while others support only single data source.

• Backup and Recovery:  Even though the complete loss of data is less common with data warehouses, it is vital to choose a platform that stores your backup to S3 allows you to use such information at any time. 

• Company size: Large size organizations need to choose a data platform with the following features, hybrid transaction/analytical processing (HTAP), analytical database, and relational DBMS. 

Five factors to help select the right data warehouse product

Whether you are buying a new data warehouse platform or expanding on an existing one, it is vital to ensure that you choose the right warehouse product which meets the need of your organization.

Here are five factors that can help you select the right data warehouse for your company

 • Size of your company: Large organizations that want to deploy the use of a data warehouse platform need products that can accept data from multiple sources coupled with that which has an analytical DBMS through which traditional and non-traditional queries can be processed. Mid-sized organizations, on the other hand, where there are flexibility need products that are compatible across different platforms. While smaller organizations with minimal IT support those must consider cloud data warehouse as a service offering

• Consider your availability and performance need: When performance becomes a priority for your organization, you may have to opt for on-premises deployment because data warehouse platforms are slow due to lower speed imposed by network latency with cloud access. However, on-premises deployment delivers faster performance for you and increases system availability. 

• Is your business cloud ready? Data warehouse platform is the best option for businesses that are already in the cloud. Although, there are big data warehouse platforms that offer cloud-based deployment like Microsoft Azure SQL Data Warehouse, while Amazon Redshift, IBM dashDB offers a cloud-only option.

• Latency requirement and data volume: You must also consider your latency requirement and data volume before opting for a data warehouse product. This is because as data volume requirement reduces, there are more varied options which can be utilized, including data warehouse appliances. 

• What is your big data strategy? If a data warehouse platform is part of your big data strategy, then you may have to search for products that allow you to integrate unstructured and multimedia data into the warehouse. The products must also manage and utilize this type of data; for instance, platforms like IBM, Microsoft, and Oracle are integrating support for non-traditional data into their products. 

The leading data warehouse platforms

Actian Analytics Platform Appliance

Actian Analytics platform combines columnar and relational database capabilities and provides high-speed data warehouse implementation and management to its users. The platform is also designed to provide enterprise-grade SQL and high performance to all business users. Some of its features include data blending, data integration, discovery analytics, and easy-to-use workbench.  

Action Analytics platform has four major components, which include:

• Actian Dataflow: It allows elastic data preparation, which will enable customers to bring their data for ingestion using the Konstanz Information Miner open source data analytics, and integrated user interface.

• Actian Vector:  This is a fast, and symmetric multiprocessing relational database system, designed for data analytics that runs on modern commodity hardware. 

• Actian Matrix: Actian Matrix is designed for complex analytics to be carried out on a large amount of data. The architecture allows more users, linear scaling, and more analytics

• AAP: AAP provides every business with security capabilities, which include role separation, flexible encryption, security auditing, discretionary access control, Integration with enterprise authentication, and Active Directory.

Microsoft Azure SQL Data Warehouse

This incredible data warehouse platform is designed to allow independent scaling of data based on your performance need so that you pay for query performance when you need only. It is a fully managed data warehouse which has been integrated into the Microsoft SQL Server ecosystem to provide all businesses with a distributed database management system which can store both relational and nonrelational data. 

  • Some of its features include:
  • Microsoft Azure SQL Data Warehouse uses Microsoft processing architecture and SQL Server’s column store index technology to deliver performance. 
  • It also features SQL Database, T-SQL, SQL Server, SQL Data Warehouse, and Microsoft Analytics Platform System, which helps customers to develop solutions that meet their need. 
  • It enables customers to query nonrelational data.

IBM dashDB

This is a managed cloud warehouse platform perfect for database administrators,  business analysis, data scientists, developers. The platform can be used to build new solutions, applications, and architecture; it is also designed to ensure rapid business intelligence and analytics delivery despite the limitation in any existing organizational infrastructure.

Some of its features include:• It provides multiple data processing, single instruction, in-memory capabilities, data skipping through its  DB2 with BLU Acceleration.• It also has an in-database which allows users to analyze warehouse data using built-in IBM Netezza Analytics (INZA) functions.• In addition, this unique database is capable of processing unstructured data because it gives room for direct integration to IBM Cloudant.

IBM PureData System for Analytics

This data warehouse platform is designed to deliver standard based warehouse with analytics capabilities that help end users to get results quickly while executing complex queries.  It also provides standards-based data warehouse and analytics capabilities; the applicable integrates works with a database management system servers, storage and advanced capabilities int to a single system. Some of its features include:

  • It provides a purpose-built appliance for data warehousing that is complete and secure
  • It is designed for high-performance analytics, the architectures use Snippet processing units from Netezza which engineers fast performance processing of large volume of data
  • It provides in-database analytics function which helps clients to write customized functions through user-defined extensions. 

Redshift cloud data warehouse

This data management warehouse helps organizations to analyze data in a cost-effective way using intelligence business tools. It is a hosted and large scale data warehouse designed for the analytic workload.

Some for the features of Redshift cloud data warehouse includes:• It offers parallel processing of data which is built on column-oriented DBMS, and enables the faster processing of queries across multiple nodes.  • It’s built on hardware designed for his performance data processing• It has an architecture that allows the automation of administrative task, and configuration of data warehouse on the cloud.• It offers built-in enterprise security with features that include cluster isolation using Amazon Virtual Private Cloud, Secure Sockets Layer protocol,in-transit using hardware-accelerated Advanced Encryption Standard,  and critical management using AWS Key Management System.

HPE Vertica Analytics Platform

This unique platform from Hewlett Packard Enterprise is designed for complex and query intense applications. It is a relational database system that is built for modern analytical workloads; it makes use of a clustered approach in the storage of big data and delivers high-performance query and analytical functionalities. It enables companies to reserve their investment by delivering relational database management system which has the full support of  Java Database Connectivity (JDBC), SQL, and Open Database Connectivity (ODBC). 

  • Some of its features include• HPE Vertica platform delivers support for Hadoop; it also allows queries to be executed on all files and provides significant support in performance over the traditional Hadoop access.
  •  It helps users index large log files data like those created through the networked system and identify failures and cyber attacks as well as investigating unauthorized access.
  • It has an improved SQL analytics features that enhance the large library of built-in analytical function which ranges from relational online analytics processing to other forms of data
  • It also delivers improved manageability with an enhanced security system, backup, and recovery, role-based access, automated maintenance groups, among others.
  • It is a distributed database that is designed to work on a cluster of inexpensive of the self server, the platform help businesses to reduce scaling cost when compared to traditional databases.

Conclusion

Finally, data warehouse is of great importance to every organization. At present, there are large numbers of options available when choosing the best data warehouse platform for your organizations, and that is why you must take a careful look at your organization and choose a warehouse that is consistent with the need and goals of your firm. 

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