X
Start evaluating software now

 Security code
Already have a TEC account? Sign in here.
 
Don't have a TEC account? Register here.

Human Resources (HR)
Human Resources (HR)
Human Resources encompasses all the applications necessary for handling personnel-related tasks for corporate managers and individual employees.  Modules will include Personnel Management, ...
 

 etl perspectives on data warehousing

Business Intelligence (BI) RFI / RFP Template

Reporting and Analysis, Analytics, Data Warehousing, Workflow, Data Integration, Support, and System Requirements Get this template

Read More
Start evaluating software now

 Security code
Already have a TEC account? Sign in here.
 
Don't have a TEC account? Register here.

Human Resources (HR)
Human Resources (HR)
Human Resources encompasses all the applications necessary for handling personnel-related tasks for corporate managers and individual employees.  Modules will include Personnel Management, ...

Documents related to » etl perspectives on data warehousing

Best Practices for a Data Warehouse on Oracle Database 11g


Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

etl perspectives on data warehousing  used to limit the ETL processes to nodes 1 and 2 in the cluster and Ad-hoc queries to node 3 and 4. Workload Monitoring In order to have an overall view of what is happening on your system and to establish a baseline in expected performance you should take hourly AWR or statspack reports. However, when it comes to real-time system monitoring it is best to start by checking whether the system is using a lot of CPU resources or whether it is waiting on a particular resource and if so, what is that Read More

Business Intelligence: A Guide for Midsize Companies


Business intelligence (BI) is not a new concept. What’s new is that BI tools are now accessible for midsize companies. Managers can use BI to analyze complex information to support their decision-making processes, combining data from a variety of sources to get an integrated, 360-degree view of the company. Find out how to select the right BI software, the right vendor, and the right approach to implementing BI.

etl perspectives on data warehousing  enterprise data warehousing | etl data warehouse | financial data warehouse | future of data warehousing | inmon data warehouse | introduction to data warehouse | metadata data warehouse | metadata warehouse | ods data warehouse | olap data warehouse | open source data warehouse | operational data warehouse | real time data warehousing | staging warehouse | star schema data warehouse | virtual data warehouse | what is data warehouse | what is data warehousing | BI active data warehouse | BI active data Read More

Unlocking Hidden Value from Investments in SAP NetWeaver Business Warehouse


Extending the capabilities and value of SAP NetWeaver Business Warehouse is a concern for users. To improve data use and fact-based decision making, and reduce stranded spreadsheets, SAP users can choose a business intelligence (BI) software solution such as IBM Cognos 8, with budgeting, planning, and forecasting functions. Find out more about how you can improve your business performance management content with BI.

etl perspectives on data warehousing  Transformation and Load | ETL Layer | Data Reporting | Data Migration | SAP Business Intelligence Tools | BW Accelerator | Business Intelligence Data Warehouse | BI Accelerator | Business Intelligence Software Providers | Online Analytical Processing | Data Warehouse Software | Business Intelligence Reporting Software | Business Intelligence White Paper | Ad-hoc Data Marts | Avoid Stranded Data | SAP Netweaver Advantages | Remodeling Data | Corporate Data Sources | Data in SAP and Non-SAP Systems | Read More

Contemporary Business Intelligence and Its Main Components


Business intelligence (BI) represents the tools and systems that play a key role in the strategic planning process by allowing a company to manipulate corporate data for decision-making. But what exactly are the primary components of BI?

etl perspectives on data warehousing  also different from conventional ETL tools for data warehousing because it neither moves data nor creates new data stores of integrated data. Rather, it leaves data where it is, leveraging metadata repositories across multiple foundation enterprise systems, and visibly pulls information into new applications. As a result, customers may be content to trade in expensive DWs for a data extraction and presentation layer that sits on top of existing transactional systems—but only on the condition that they Read More

Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

etl perspectives on data warehousing  data management analysis software selection,data analysis management solution evaluation,compare most accurate data tools, statistics application selection,statistical methods,improve data management and analysis,rfp to manage data,ecm software evaluation,information security is,compare information security systems,document management systems,dms,dms selection,is solution comparisons,product information management solution selection,pim,enterprise content management ecm,electronic media files,pim solution selection,compare top access control files software,security,evaluate data delivering systems,business analysis reports,dmag,analyse statistics,methodology,evaluate information security systems. Read More

Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

etl perspectives on data warehousing  Enterprise Management Associates, EMA, 9sight Consulting, big data, hybrid data ecosystem, real-time data, big data buzz, big data requirements, big data challenges, big data architecture Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

etl perspectives on data warehousing  data quality assurance plan,data quality assurance process,data quality assurance techniques,data quality attributes,data quality audit,data quality audits,data quality benefits,data quality best practices,data quality blog,data quality books,data quality business intelligence,data quality campaign,data quality center,data quality certification,data quality challenges Read More

Demystifying Data Science as a Service (DaaS)


With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

etl perspectives on data warehousing  data science, big data, analytics, data SaaS, data scientist, India, data as a service, real-time data, data analytics Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

etl perspectives on data warehousing  The selection of the ETL tool requires an understanding of the source data feeds. The following issues should be considered: Many warehouses are built from legacy systems that may be difficult to access from the computer network. ETL tools often do not reside on the same machine as the source data. The data structures of the legacy systems may be hard to decompose into raw data. Legacy data is often dirty (containing invalid data, or missing data). Care must be taken in the evaluation of the tool to Read More

Data Quality: A Survival Guide for Marketing


Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

etl perspectives on data warehousing  data quality jobs,data quality solution,data quality methodology,data quality strategy,address data quality,data quality manager,data quality audit,data quality measurement,what is data quality,data quality in data warehouse,data quality dashboard,data quality program,clinical data quality,improving data quality,data quality measures Read More

Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations


While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of "big data" and the use of analytics to mine that data.

etl perspectives on data warehousing  big data analytics,about data mining,advanced analytic,advanced analytics,advanced analytics definition,advanced analytics techniques,advanced data analytics,analytic data,analytic database,analytic databases,analytical data,analytical database,analytical software,analytics,analytics business Read More

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

etl perspectives on data warehousing  data blending, data analyst, data source, data analysis, data software, data cleansing, data access, data blending software Read More

Ramco HCM on Cloud Is on a Roll in the Middle East; Africa


Ramco Systems, an enterprise software vendor that has lately been focused on delivering enterprise resource planning (ERP) in the cloud and on tablets and smartphones, recently showcased its all new HR and talent management solution, Ramco HCM on Cloud (HCM standing for human capital management). Since the global launch of Ramco HCM on Cloud in June 2013, Ramco has added some of the largest

etl perspectives on data warehousing   Read More