markdown Dallas Data Brewery聚会小组回答

Posted 2021-05-06

What tools do you use?
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- Propreitary Software, R, Python, SQL, Gephi
- Tableau; Excel; Access
- SPSS in the application of psych statistics and research methods
- Tableau, SQL, SPSS, R and other statistical tools.
- SSMS, R, SSAS
- Python, Matplotlib, Disco...
- Proprietary
- R, SPSS, SAS, Relational DB
- SPSS; SAS; SQL; SSRS; R
- Excel, Excel Miner, SAS, Stastica
- Whatever is necessary.  Everything from databases to data analytics solutions.
- Perl, CGI, Ajax.
- Erlang
- Brain (other tools)
- PHP, JavaScript, MongoDB, Beanstalkd, MapReduce.
- R, Orange, Weka, TIBCO Spotfire
- SAP HANA, NoSQL, Mongo, Azure, Hadoop
- Excel (of course), Teradata, Essbase, Tableau
- Postgres, Pentaho, PRD, Kettle
- various
- Servers, Crystal reports, Kpi, Map info 
- No special tools -- could be a text-handling language like AWK, or a special library (e.g., Regular Expression) of a particular programming language.
- Drupal, CiviCRM, MySQL, PHP
- Java, javascript


What are you doing with data?
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- Business Intelligence, Process Analytics, Statistical Analysis, Data Mining
- Visual analytics; data analysis.
- reading about big data analytics, wishing for useful tools to study and handle data for use in the workforce
- I use data to better understand trends and patterns within the behavior of the systems that I monitor on a daily basis
- Archival/analysis
- Cleansing, Plotting, Modeling
- We are trying to link data that is captured by customer, aligning it to data captured outside of our domain in order to create a buying profile to leverage for marketing.
- Advanced Analytics
- Building predictive models to determine which new markets  my company should enter.
- I am trying to understand the co-relations
- Everything in the data management lifecycle.
- MySql, Regular Expressions, Web data scraping.
- Grinding bytes into bits
- Assessing possible outcome based on the data collected for the study. 
- Providing automated analysis of social media
- Build data models as hobby, would like to make it a career.
- Consuming it
- Large-scale analytics from high-transaction volume real-time systems.
- Working to establish Data Governance so we have quality information to make better decisions with.
- Fixing, fixing, fixing
- databases  and programming
- Kpi, key performance indicators, Stats, Forecast, Store

- Good question.  Data is all around, but we often either ignore it, or don't get the full use out of it (such as coming up with conclusions, based on its attributes).
- Building customized data organizational structures and their user interfaces and displays
- Providing end user access to data (automatically generating SQL), both from Natural Language and visual methods.


What would you like to learn to do?
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- More insight into analytics.
- I basically said what above
- I would like to learn new data models and methods
- See what other people are using/doing for their data projects.
- Parse the external data quickly and efficiently to glean the valuable data
- Open Data
- utilize open source tools in my data analysis
- I would like to learn how i can use the Data from the better ness of the business
- Log onto secure websites programmatically.
- Move my interest into the 21st century with the appropriate tools and techniques
- Better analysis
- Understand others experiences bridging transaction processing and analytics requirements.
- Learn how companies are handling the data gathering and processing to get their  'hands on the data' faster than traditional BI approaches offer.
- Create awesome reports
- Interface with other database experts


What issues do you face while working with data?
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- data cleansing issues.
-  I'm a really smart, fast learner
- One of the obstacles I face with data is being able to think of a clear path that enables me to transform the data into knowledge 
- Issues related to performance and analysis of data.
- 80% of my time is cleaning data
- Too much cruft in social media.
- Accessibility and User Education
- Incomplete data; poor table and database design.
- Unable to under what the output i am getting from the input that i am feeding
- Data cleanliness, identifying and structuring data according to organizational needs, delivering cost-effective solutions.
- Would like someone to pay me for my efforts. <GRIN>
- Having to sleep
- Becoming more efficient!
- Rate limits, conveying insight, visualization.
- Too many to list here
- Comprehensio
- Non-standard toolsets, immature presentation tools.
- Primarily it is the incompleteness of the data and consistent definitions.
- visualization
- Sorting, manipulation, monitoring, reading, 
- Its format, more than anything else.  It can be pure ASCII (or EBCDIC) text, stored as machine integers (big- or little-endian), floating point, bcd, or even something else.
- Limited users for BI tools (must be database-savvy to write SQL)