This Week in Data Preparation (July 13, 2020)
9 links in this week’s post: 1 company announcement (our paradigm-shifting Data Preparer platform is now available to try in AWS, Azure and on Premise), 1 survey on the state of data science by Anaconda, 1 tutorial on data prep by Microsoft Research, and 6 opinion articles featuring a number of domain experts, on self-service ingestion, citizen data scientists, data analytics, and customer data platforms.
The Data Value Factory Launches Data Preparer on AWS and Microsoft Azure. “This cloud offering comes as a natural next step in our line of work towards embracing data democratisation,” said Dr. Nikolaos Konstantinou, Managing Director at The Data Value Factory. “Our goal is to provide a self-service data prep solution that can be deployed virtually anywhere, and connect to a wide range of databases and file formats, at a competitive price,” he commented.
Data Prep Still Dominates Data Scientists’ Time, Survey Finds. “Data science has the ability to be transformational for businesses, but our 2020 survey shows that both organizations and professionals in the space are still in the process of maturing,” Anaconda CEO and Co-Founder Peter Wang states in a press release.
Data Prep for Machine Learning: Missing Data. Turning his attention to the extremely time-consuming task of machine learning data preparation, Dr. James McCaffrey of Microsoft Research explains how to examine data files and how to identify and deal with missing data.
Self-Service Ingestion: The Key to Creating a Unified, Scalable, Cloud Data Lake. “Self-service ingestion helps enterprises capture, enrich, and process data smoothly and free up data and IT pros to focus on higher-value tasks.” claims P. C. Kiran, head of the big data engineering practice at Impetus Technologies Inc.
How to cultivate citizen data scientists in midsize companies. “These individuals [citizen data scientists] demonstrate that anyone with analytical capabilities can become champions for data-driven decision making. This upskilling is ultimately the key to driving data-backed business innovation which will improve the companies’ competitive stance.” writes Jens Krueger, Chief Technology Officer, EMEA at Workday.
Taming analytics in a data-driven world. 4 experts comment in this article by Kirsten Doyle, ITWeb contributor:
- “Businesses can utilise data visualisation for their broader team to consume mass amounts of data and make informed decisions faster.” says Melissa Jantjies, senior associate systems engineer at SAS, adding that not everyone can be a data specialist who develops BI reports.
- Paul Morgan, business unit lead for Data, Planning, and Analytics at Altron Karabina, says data can also be used to understand poor performance in certain areas of the business.
- It has been proven repeatedly that understanding the business and its client base allows it to progress and adapt to the ever-changing landscape, adds Archana Arakkal, machine learning engineer at Synthesis Technologies.
- “Effectively analysing data can produce insights the business did not previously hold,” adds Andreas Bartsch, head of Service Delivery at PBT Group.
The Best Way to Get Started with Data Analytics. 6 domain experts comment in this article by John Edwards, a veteran business technology journalist:
- To introduce data analytics effectively, enterprises need to develop a strategy that promotes both top-down and bottom-up initiatives, said Gonzalo Zarza, director of data and analytics for IT and software development company Globant.
- Begin the journey into data analytics by building a strong foundation, advised Rosaria Silipo, principal data scientist at KNIME, an open source data analytics company.
- Follow up by building an inventory of existing resources and capabilities, including whatever is available in the current data warehouse, the organizational structure and from staff competence. “A useful guide for this purpose is the Analytics Maturity Model developed by INFORMS, a leading academic and professional analytics organization,” said Willem van Hoeve, a professor of operations research and head of the master of science in business analytics program at Carnegie Mellon University’s Tepper School of Business.
- Most enterprises have collected a significant amount of data but don’t really know it, since it’s most likely siloed between different departments. “If they haven’t done anything with data analytics, there’s a good chance that individual departments have taken the initiative to build or purchase their own solutions,” said Zach Reece, a former Deloitte CPA.
- Choose a specific business problem that data analytics can solve, and build a solution for that problem, advised David Linthicum, chief cloud strategy officer for Deloitte.
- Shervin Khodabandeh, a data analytics expert at management consulting firm Boston Consulting Group, recommended focusing on a handful of large initiatives, rather than several smaller projects, and securing senior management sponsorship.
The intricacies and benefits of customer data platforms. “For data-driven marketers, getting their martech stack right can unlock the door to transformational customer experiences. In an ideal martech environment, where all platforms are tied together by a unified data framework & foundation, the entire business can benefit from real-time informed insight.” explains Jason Skelton, Head of Platform Alliances at Acxiom.
7 Customer Data Platform (CDP) Implementation Tips. “The biggest mistake companies make with CDP implementations is not bringing IT and marketing teams together to make sure the implementation delivers the promised benefits of the investment,” said Raj Kini, director of professional services of Arm Treasure Data, which offers CDP software solutions.
Thank you for taking the time to read our weekly post with news items from the data preparation market.
