In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject. He also provides an assessment of the risks organizations face in working with data lakes and offers recommendations for maximizing the potential of data.
Topics: Big Data, Data Warehousing, Analytics, Business Analytics, Business Intelligence, Data Governance, Data Management, Data Preparation, data lakes
This year, Teradata rebranded the Teradata users conference from "Partners" to "Analytics Universe", and there is a reason for it. For decades, Teradata has represented the high end of the analytic database, but new innovations and technologies are adding flexibility to Teradata's licensing as they compete. For the full breakdown of Teradata's Analytics Universe 2018, and my analysis of all the largest announcements, watch my hot take video.
Topics: Big Data, Data Warehousing, Teradata, Analytics, Data Governance, Data Management, Data Preparation, Information Management, Data, Digital Technology
Big data was big news in 2012 and probably in 2013 too. The Harvard Business Review talks about it as The Management Revolution. The Wall Street Journal says Meet the New Boss: Big Data, and Big Data is on the Rise, Bringing Big Questions. Given big data’s popularity in the press, you might think that the technology market is only about big data and how companies use the vast and growing amount of data now available to organizations. While this technology can provide a significant opportunity, the reality is that just having big data does not provide an organization with the intelligence to be more efficient or grow market share. It can provide the foundation on which organizations can assemble technologies and applications that can help realize these opportunities, but organizations need to focus on the big picture, which encompasses additional layers of technology that work together with big data. Our recent benchmark research on business technology innovation found that big data is not the top priority for business or IT; analytics, collaboration, mobile and cloud computing are all more important. Organizations do believe that big data is very important (25%), but if they were pushed to prioritize technologies, it would not top the list.
Topics: Big Data, Data Warehousing, Predictive Analytics, Social Media, Harvard Business Review, Wall Street Journal, IT Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Information Management, Technology Innovation, Strata+Hadoop
Kognitio Brings Big Data Experience to Business Analytics
Kognitio has been serving the analytics and data needs of organizations for more than 20 years with an in-memory analytics platform that meets many of the big-data needs of today’s organizations. Kognitio Analytical Platform provides a unique massively parallel processing (MPP) in-memory database that can rapidly load data and calculate analytics; it is available both in an analytical software appliance and via cloud computing.
Topics: Big Data, Data Warehousing, Social Media, alteryx, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Hortonworks, Information Management, Kognitio, Strata+Hadoop
At first I thought 1010data just developed a faster data warehouse technology to be used with business intelligence tools. After a recent briefing, however, I learned that it provides much more than a data warehouse; the product is a large-scale analytics server that empowers business analysts to work on big data, conducting for, example, market basket analysis or correlations of customer and product information. The software lets organizations retain and analyze more data and increase the speed of analysis, which our benchmark research on big data found to be the top two benefits of the technology for more than 70 percent of organizations.
Topics: Big Data, Data Warehousing, Sales Performance, Predictive, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Information Management
My colleague Mark Smith and I recently chatted with executives of Tidemark, a company in the early stages of providing business analytics for decision-makers. It has a roster of experienced executive talent and solid financial backing. There’s a strategic link with Workday that reflects a common background at the operational and investor levels. As it gets rolling, Tidemark is targeting large and very companies as customers for its cloud-based system for analyzing data. It can automate alerts and enhance operating visibility, collaboratively assess the potential impacts of decisions and support the process of implementing those decisions.
Topics: Big Data, Data Warehousing, Master Data Management, Performance Management, Planning, Predictive Analytics, Sales Performance, GRC, Budgeting, Risk Analytics, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Customer & Contact Center, Data Governance, Data Integration, Financial Performance, In-Memory Computing, Information Management, Mobility, Workforce Performance, Risk, Workday, Financial Performance Management, Integrated Business Planning, Strata+Hadoop
Kalido recently introduced version 9 of its Information Engine product. The company has been around for 10 years but has had difficulty establishing its identity in the information management market. Kalido was perhaps ahead of its time, partly a vendor of data integration, partly master data management and partly data governance. As an example of the positioning challenge, its core product, Information Engine, while not a data integration tool, could in some cases provide sufficient capabilities to meet an organization’s data integration needs. Its real value, however, comes from authoring and management of information about the user’s data warehouse.
Topics: Data Quality, Data Warehousing, Master Data Management, Data Governance, Data Integration, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Kalido
Teradata: All in the Family of Appliances and Big Data
Teradata recently held its Partners User Group meeting (Twitter hashtag #TDPUG11) in San Diego. Analysts were briefed previously on some of the announcements, which I covered in an earlier post.
Topics: Big Data, Data Warehousing, Predictive Analytics, Sales Performance, Supply Chain Performance, Teradata, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Workforce Performance, Digital Technology
Recently Karmasphere introduced version 1.5 of its Analyst product which helps organizations analyze “big data” stored in Hadoop, the open source large-scale data processing technology. An independent software vendor focused exclusively on the Hadoop market, Karmasphere made available a community edition of its developer product in September 2009 and launched the company in March 2010. Since then it has been active and visible in Hadoop-related events including Hadoop World, the IBM Big Data Symposium and others.
Topics: Big Data, Data Warehousing, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Karmasphere, Workforce Performance, Strata+Hadoop
There has been a spate of acquisitions in the data warehousing and business analytics market in recent months. In May 2010 SAP announced an agreement to acquire Sybase, primarily for its mobility technology and had already been advancing its efforts with SAP HANA and BI. In July 2010 EMC agreed to acquire data warehouse appliance vendor Greenplum. In September 2010 IBM countered by acquiring Netezza, a competitor of Greenplum. In February 2011 HP announced after giving up on its original focus with HP Neoview and now has acquired analytics vendor Vertica that had been advancing its efforts efficiently. Even Microsoft shipped in 2010 its new release of SQL Server database and appliance efforts. Now, less than one month later, Teradata has announced its intent to acquire Aster Data for analytics and data management. Teradata bought an 11% stake in Aster Data in September, so its purchase of the rest of the company shouldn’t come as a complete surprise. My colleague had raised the question if Aster Data could be the new Teradata but now is part of them.
Topics: Data Warehousing, Microsoft, RDBMS, SAS, Teradata, IT Performance, Business Intelligence, Cloud Computing, Data Management, HP, IBM, Information Management, Oracle
Secrets Revealed in Columnar Database Technology
This is the second in a series of posts on the architectures of analytic databases. The first post addressed massively parallel processing (MPP) and database technology. In this post, we’ll look at columnar database technology. Given the recent announcement of HP’s plan to acquire Vertica, a columnar database vendor, there is likely to be even more interest in columnar database technology, how it operates and what benefits it offers.
Topics: Data Warehousing, RDBMS, IT Performance, Business Intelligence, Cloud Computing, Data Management, Information Management
Living in the Era of Hadoop and Large-Scale Data
It’s clear that now we are living in the era of big data. The stores of data on which modern businesses rely are already vast and increasing at an unprecedented pace. Organizations are capturing data at deeper levels of detail and keeping more history than they ever have before. Managing all of the data is thus emerging as one of the key challenges of the new decade.
Topics: Data Warehousing, RDBMS, IT Performance, Business Intelligence, Cloud Computing, Data Management, Information Management, Strata+Hadoop
Kognitio Pablo Brings MDX to Data and Analytics
Kognitio announced the addition of MultiDimensional eXpressions (MDX) capabilities for its WX2 product line. John Thompson, CEO of U.S. operations, and Sean Jackson, VP of marketing, shared some of the details with me recently. I find the marriage of MDX and large-scale data both technically challenging and potentially valuable to the market.
Topics: Data Warehousing, MDX, RDBMS, IT Performance, Business Intelligence, Data Management, Information Management, Kognitio, MPP
MicroStrategy Combines Actions with Business Intelligence and Mobility
Last week I attended MicroStrategy World 2011 in Las Vegas, the North American version of the business intelligence (BI) vendor’s annual user conference. The event was well attended, and the company claimed attendance was up 40% over last year. The purpose of the post is to recap the announcements made, highlight the areas where MicroStrategy is making investments and comment on the overall direction implied by these investments.
Topics: Data Warehousing, MicroStrategy, IT Performance, Analytics, Business Intelligence, Cloud Computing, Data Management, Information Management
Jaspersoft Releases Version 4 and Tackles Large-Scale Data
Open source business intelligence (BI) software vendor Jaspersoft recently announced general availability of its flagship product Jaspersoft 4 and earlier this week announced a new reporting project that provides data connectors to a variety of large-scale data sources.
Topics: Data Warehousing, IT Performance, Analytics, Business Intelligence, Cloud Computing, Data Management, Information Management
Secrets Revealed in Massively Parallel Processing and Database Technology
This is the first in a series of posts on the architectures of analytic databases. This is relational database technology that has been “supercharged” in some way to handle large amounts of data such as typical data warehouse workloads. The series will examine massively parallel processing (MPP), columnar databases, appliances and in-database analytics. Our purpose is to help those evaluating analytic database technologies understand some of the alternative approaches so they can differentiate between different vendors’ offerings. There is no single best solution for all analytics for all types of applications; usually the decision involves a series of trade-offs. Understanding what you might be giving up or gaining, you may be able to make a better decision about which solution is best for your organization’s needs.
Topics: Data Warehousing, RDBMS, IT Performance, Business Intelligence, Cloud Computing, Data Management, Information Management
HP Gives Up on Business Intelligence and Analytics Markets
No one has seemed to notice that in the last several months, Hewlett-Packard has quietly made changes to its participation in the enterprise software market; this will significantly change HP’s value for CIOs and IT organizations in regards to business intelligence (BI) technologies.
Topics: Data Warehousing, IT Performance, IT Research, Operational Performance, Analytics, Business Intelligence, Business Performance, Enterprise Software, Governance, Risk & Compliance (GRC), HP, Information Applications, Information Management, HP Neoview
IBM Makes Major Buy in Analytics Market with Netezza
IBM has announced its intention to acquire Netezza, one of the world’s fastest-growing providers of data appliances, for approximately $1.7 billion. Founded only 10 years ago, Netezza has over 500 employees and 350 clients including brand names Burlington Coat Factory, Con-way Freight, Estee Lauder, Marriott and Nationwide Insurance. IBM has been investing in analytics software for five years and now becomes one of the strategic providers in the market. Many organizations are unwilling to spend the large amount of resources and budget to configure and tune complex databases like Microsoft, Oracle’s and even IBM on a specific brand of hardware and then have to deal with issues in storage, performance and scalability in processing data across their network. Instead they would like to find a technology package that handles data simply for various analytic purposes and is as easy to buy as a dishwasher or a clothes dryer.
Topics: Data Warehousing, Analytics, Business Intelligence, Information Management, Netezza
IBM Makes Major Buy in Analytics Market with Netezza
IBM has announced its intention to acquire Netezza, one of the world’s fastest-growing providers of data appliances, for approximately $1.7 billion. Founded only 10 years ago, Netezza has over 500 employees and 350 clients including brand names Burlington Coat Factory, Con-way Freight, Estee Lauder, Marriott and Nationwide Insurance. IBM has been investing in analytics software for five years and now becomes one of the strategic providers in the market. Many organizations are unwilling to spend the large amount of resources and budget to configure and tune complex databases like Microsoft, Oracle’s and even IBM on a specific brand of hardware and then have to deal with issues in storage, performance and scalability in processing data across their network. Instead they would like to find a technology package that handles data simply for various analytic purposes and is as easy to buy as a dishwasher or a clothes dryer.
Topics: Data Warehousing, Analytics, Business Intelligence, Information Management, Netezza