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.
Read More
Topics:
Big Data,
Data Warehousing,
Analytics,
Business Analytics,
Business Intelligence,
Data Governance,
Data Management,
Data Preparation,
data lakes
Effectively managing data privacy and security is a high-stakes matter. When an organization doesn’t get it right, it often becomes front-page news and occasionally becomes a subject of litigation. Yet organizations face an equally challenging imperative to ensure that business users have easy access to the data they need. Depending on how they are implemented, data governance policies can inhibit access to data, making it harder to find and utilize the data assets of an organization.
Read More
Topics:
Big Data,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Internet of Things
Artificial intelligence (AI) and machine learning (ML) are all the rage right now. Our Machine Learning Dynamic Insights research shows that organizations are using these techniques to achieve a competitive advantage and improve both customer experiences and their bottom line. One type of analysis an organization can perform using AI and ML is predictive analytics. Organizations also need to plan their operations to predict the amount of cash they will need, inventory levels and staffing...
Read More
Topics:
Office of Finance,
Analytics,
Business Intelligence,
Financial Performance Management,
Digital Technology,
Predictive Planning,
AI and Machine Learning
I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.
Read More
Topics:
Analytics,
Business Intelligence,
Data Governance,
Data Preparation,
Data,
Information Management (IM),
Digital Technology,
data lakes,
AI and Machine Learning
MicroStrategy recently held its annual user conference, which focused on the theme of the “Intelligent Enterprise.” HyperIntelligence, an innovative product for delivering analytics throughout organizations that they introduced a year ago, was the star of the event. The company announced enhancements to HyperIntelligence and the latest version of its flagship platform, MicroStrategy 2020, as well as a new two-tiered education and certification program.
{% video_player "embed_player"...
Read More
Topics:
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data,
Digital Technology,
Conversational Computing
Ventana Research recently announced its 2020 research agenda for analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from their technology investments and improve business outcomes.
It’s been exciting to follow the emergence of innovative capabilities in the analytics market, but for businesses it can be challenging to stay on top of all these changes. To help, we craft our research agenda using our firm’s knowledge of technology...
Read More
Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Internet of Things,
natural language processing,
AI and Machine Learning
For years I’ve viewed with skepticism the claim that one technology or another will reduce audit costs. For one, there’s rarely a silver bullet. An array of moving parts drive audit fees. For example, the complexity of the corporation, accounting data management and the audit staff’s familiarity with the industry and the company all affect the time auditors must spend. Also, most of the time I’ve found that achieving significant savings was not the result of going from good to great, but from...
Read More
Topics:
Office of Finance,
Analytics,
Business Intelligence,
Financial Performance Management,
ERP and Continuous Accounting,
robotic finance,
AI and Machine Learning
Using customer analytics effectively involves several challenges. Organizations must make it a business priority, cultivate leadership and set a course for ensuring data and analytics are being processed and governed effectively. But effectiveness also requires technology that will assist in the effective operations and management of customers and help an organization achieve its goals.
Read More
Topics:
Customer Experience,
Voice of the Customer,
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Contact Center,
Data,
Digital Technology,
Digital Commerce,
blockchain,
natural language processing,
data lakes,
Intelligent CX,
Conversational Computing,
collaborative computing,
mobile computing,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
Customer analytics have never been more important, but effectively creating and managing them is not easy. The data that’s required to achieve visibility into all customer activity involves many applications and systems and it’s a challenge to ensure the data used is accurate and consistent. Even once data is assembled, organizations often struggle to apply analytics to create the metrics that best represent an understanding of the past and, more importantly, the path to the future.
Read More
Topics:
Customer Experience,
Voice of the Customer,
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Lake,
Data Preparation,
Information Management,
Contact Center,
Data,
Digital Technology,
Digital Commerce,
blockchain,
natural language processing,
Intelligent CX,
Conversational Computing,
collaborative computing,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
By itself, data isn’t useful for business; the application of analytics is necessary to transform data into actionable information. Data analysis of one sort or another has long been a core competence of finance departments, applied to balance sheets, income statements or cash flow statements. Today, however, Finance must go beyond these basics by expanding the scope of the data being examined to include all financial and operational information that can yield actionable insights. Analysis thus...
Read More
Topics:
Customer Experience,
Human Capital Management,
Voice of the Customer,
embedded analytics,
Learning Management,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Lake,
Data Preparation,
Information Management,
Internet of Things,
Contact Center,
Data,
Product Information Management,
Sales Performance Management,
Workforce Management,
Financial Performance Management,
Price and Revenue Management,
Digital Technology,
Digital Marketing,
Digital Commerce,
ERP and Continuous Accounting,
blockchain,
natural language processing,
robotic finance,
Predictive Planning,
candidate engagement,
Intelligent CX,
Conversational Computing,
Continuous Payroll,
revenue and lease accounting,
collaborative computing,
mobile computing,
Subscription Management,
total rewards management,
intelligent marketing,
intelligent sales,
AI and Machine Learning