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10 Data and Analytics Trends in 2020

The importance of data and analytics will continue to grow in 2020 and there are ten trends your organization should take note of to stay competitive. In the video below, I’ve outlined these ten trends and what you can do to stay on top of them. 10 Data and Analytics Trends in 2020 [Video] Data […]

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Data Quality Improvement is Key to Successful Data Governance

The goal of any data quality program is to improve quality of data at the source. Once a financial institution’s data lineage capabilities are in place, a key starting point for data quality initiatives is the confirmation of critical data attributes for each major business line and functional area. The data quality program should define […]

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Driving Better Decisions with Data Governance

The business capabilities presented in our new guide demonstrates how forward-thinking financial services companies are leveraging data governance to create value for the enterprise. Accurate and timely information continues to be a key driver of enabling better decision making. Capabilities such as data principles and strategy, data architecture, organizational roles, authoritative sources, data lineage, data […]

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5 Informatica World 2018 Sessions to Improve Your Data Management

Two of the biggest data management challenges organizations face today are lack of awareness and security. Informatica World 2018, coming up in two weeks in Las Vegas, is an outstanding opportunity to learn how to mitigate these challenges, whether you’re currently leveraging Informatica tools or in the process of considering them. We’ll be there – […]

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Five Ways to Resolve Data Quality Problems in Tableau

Data sets are not static. They are constantly being updated, which can affect the quality of data. Data quality monitoring helps to resolve data issues quickly and also provides quality data. There are various ways we can resolve data issues in Tableau without changing the original data sources. Renaming We can rename fields in the Data pane […]

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Informatica Data Quality – Another Peek!

In my last blog, I presented a brief overview on Informatica Data Quality (IDQ) tools, the significance of Data Profiling and how to use the Analyst tool to profile data. In this second blog, I will introduce a few commonly used Informatica Developer tool Data Transformations. But, Why Data Transformations? Long story short, Data Quality […]

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Data Profiling through IBM Quality Stage

Many of the assumptions we have about source data are probably not accurate. Today most organizations are facing a data quality problem. In this blog we will look how we can achieve Data Quality using IBM tools. We have a two step process to achieve Data Quality: 1) Data Profiling 2) Data Quality We can […]

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Informatica Data Quality – A Peek Inside – Part 1

Data analytics, Master data management has been a top trending Business Intelligence implementation in last couple of years. One of the key success criteria for these programs is to maintain good quality data. Businesses also demand more value from the data that is maintained in the enterprise data repository. So there is a strong emphasis to […]

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Three Words for Data Quality Initiatives

Today every business is taking more and more data from various and untrusted sources system and using it in more ways than ever before. Whether it may be a small organization or an enterprise environment, data quality management is both challenging and significantly important to every business. Despite the importance, Data Quality initiatives sometimes remain […]

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Reasons for chronic Data Quality issues…

Many companies have invested millions in building a successful BI / EDW and are investing in advanced analytics for the future. But the mystery remains about the data quality. Though glaring DQ issues might be contained through constant backend data corrections or through exception handling, many organizations still faces the challenge of poor data quality. The reason Data […]

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Data Quality – Don’t Fix It If It Ain’t Broke

What is broke?  If I drive a pickup truck around that has a small, unobtrusive crack in the windshield and a few dings in the paint, it will still pull a boat and haul a bunch of lumber from Home Depot. Is the pickup broke if it still meets my needs? So, when is data […]

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Think Better Business Intelligence

by jDevaun.Photography Everyone is guilty of falling into a rut and building reports the same way over and over again. This year, don’t just churn out the same old reports, resolve to deliver better business intelligence. Think about what business intelligence means. Resolve, at least in your world, to make business intelligence about helping organizations […]

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Key strategies for Data Quality

In numerous client engagements, we have witnessed that Data Quality (DQ) is a never-ending battle. At many companies,  IT fixes and re-fixes the data rather than develop solutions and manage applications. DQ is not confined to IT, but maintaining that quality requires effort from all data users, especially those at the business end. Building a […]

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Bootstrapping Data Governance – Part I

A lot has been said and written about Data Governance (DG) and the importance of having one. However it is still a mystery for many companies to create an effective DG. Based on our experience majority of the companies in their early stages of DG fall into one of these areas: Had too many false […]

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Is IT ready for Innovation in Information Management ?

Information Technology (IT) has come a long way from being a delivery organization to an organization part of business innovation strategy, though a lot has to change in the coming years. Depending on the industry and the company culture, IT organization will mostly fall in the operational spectrum and a lot of progressive ones are  […]

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Primary Practices for Examining Data

SPSS Data Audit Node       Once data is imported into SPSS Modeler, the next step is to explore the data and to become “thoroughly acquainted” with its characteristics. Most (if not all) data will contain problems or errors such as missing information and/or invalid values. Before any real work can be done using […]

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IBM Vision 2013 – 2 thumbs Up!

I just returned from the IBM Vision Conference in Orlando, Florida. I attended a session in every available timeslot from Monday morning to Wednesday afternoon and it was worth every single minute of my time! Although there were too many sessions and presenters to mention, here are my “top picks”: Designing Solutions with IBM Cognos […]

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Introduction to Data Quality Services (DQS) – Part I

I was recently introduced to SQL Server 2012 and discovered Data Quality Services (DQS); a new feature of SQL Server 2012.  I wanted to use this blog as an introduction to DQS, define key terms, and present a simple example of the tool.  According to MSDN, The data-quality solution provided by Data Quality Services (DQS) […]

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Teradata Talks Enterprise Data Integration

Teradata has been long been known for its powerful data systems and drive to push benchmarks for large data volumes. In fact, in 1992 Teradata built a first of its kind system for Wal-Mart, capable of  handling 1 terabyte of data. One of the main advantages to routinely working with very large data sizes is the exposure to integration, data […]

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Back to the Basics: What is Big Data?

This video published by SAP provides a concise description of Big Data. Timo Elliott (SAP Evangelist) and Adrian Simpson (CTO, SAP UK& Ireland) describe the 4 major challenges that big data is comprised of: Volume – Amount of data Velocity – Frequency of change in data Variety – Both structured and unstructured data Validity – Quality of the data […]

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