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Three Keys to Better Data-driven Decisions: What You Should Know... Right Now
The perception of most small to midsized business (SMB) executives is that most of the data they need to make decisions is available “in the computer system

data driven decisions  that most of the data they need to make decisions is available “in the computer system,” or at least locked away until the moment is right for it to be accessed and used. But what if your enterprise system has not been structured to track and report this information? What if this information or metric is not even defined? Download this TEC report to find out about the three keys to better data-driven decisions—and discover how an integrated enterprise system can help you jump-start a plan for access Read More
Discrete Manufacturing (ERP)
The simplified definition of enterprise resource planning (ERP) software is a set of applications that automate finance and human resources departments and help manufacturers handle jobs such as or...
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Documents related to » data driven decisions


A Demand-driven Approach to BI
The core concept behind the Vanguard solution is that business intelligence (BI) must be demand-driven, which means that the business needs of the user dictate

data driven decisions  by making the underlying data architecture transparent to the users, who have access to information from multiple systems, platforms, or locations, and view it in a functional user interface. To that end, Vanguard's Unified Information Model (UIM) ensures that the appropriate business rules are applied and the information appears in a consistent, integrated context (whereby the user environment allows business users to identify and retrieve exactly the information they need), and provides easy-to-use tool Read More
A Road Map to Better Data-driven Decisions: Straightforward Directions for Improving Tactical and Strategic Decision Making
Small or midsize businesses need powerful yet affordable analytics, business intelligence (BI), and mobile functionality— to get the information required for

data driven decisions  decisions. You need trustworthy data from your enterprise resource planning (ERP) system, to derive insights and deliver information when and where your employees need it. For a road map for better data­driven decisions, read this report. Read More
Captured by Data
The benefits case for enterprise asset management (EAM) has been used to justify huge sums in EAM investment. But to understand this reasoning, it is necessary

data driven decisions  go to collect empirical data is driven by a combination of the perceived risk (probability X consequence), and of course the limitations set on maintenance policy design by commercial pressures. Even when all barriers are removed from the path of RCM analysts, they are often faced with an absence of real operational data on critical failures. The vast majority of the information regarding how assets are managed, how they can fail, and how they should be managed, will come from the people who manage the as Read More
Data Mining with MicroStrategy: Using the BI Platform to Distribute Data Mining and Predictive Analytics to the Masses
Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has

data driven decisions  BI Platform to Distribute Data Mining and Predictive Analytics to the Masses Data mining and predictive analysis applications can help you make knowledge-driven decisions and improve efficiency. But the user adoption of these tools has been slow due to their lack of business intelligence (BI) functionality, proactive information distribution, robust security, and other necessities. Now there’s an integrated enterprise BI system that can deliver data mining and predictive analysis. Learn more. BEGINLYXA Read More
Collecting Meaningful Data from the Web: Once an Impossibility, Now a Reality
The traditional way of extracting data from disparate data sources has been transformed by the emergence of new tools and applications, as well as the

data driven decisions  Meaningful Data from the Web: Once an Impossibility, Now a Reality   Once upon a time, organizations would extract data from several types of data sources, including different business software applications such as enterprise resource planning (ERP) systems, customer relationship management (CRM) applications, and others. Data sources also included such documents as plain-text docs and even spreadsheets. The traditional way to extract data from these sources involved a data integration Read More
Master Data Management and Accurate Data Matching
Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are

data driven decisions  Data Management and Accurate Data Matching Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process. Read More
The Teradata Database and the Intelligent Expansion of the Data Warehouse
In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role

data driven decisions  Intelligent Expansion of the Data Warehouse In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Read More
Data Management and Business Performance: Part 1-Data
Research for one of my projects led me to ask both software vendors and customers about the factors most important to software users in the selection of a

data driven decisions  BI tools to improve data management and business performance management. Consumers are continuously looking for innovative ways to move, store, and improve the quality of their data as well as to ways to capture the most valuable information for improved decision making and business performance. Let’s look at what the data tells us. Below is a Pareto chart based on data from Technology Evaluation Centers (TEC) on what software users consider to be the most popular functionality features for BI 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

data driven decisions  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. Read More
MSI Data


data driven decisions  Data Read More
Data Quality Basics
Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at

data driven decisions  Quality Basics Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue. Read More
Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise
While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to

data driven decisions  Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. Read More
Don't Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

data driven decisions  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Read More
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

data driven decisions  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More

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